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I propose a discussion on my PDF-PowerPoint "Artificial Intelligence and Education: questions, opportunities, and perspectives". I used this PDF-PowerPoint for the lecture held as keynote speaker at the International Conference "Education & Artificial Intelligence", organised on Saturday, 9th November 2024 by the FACULTY OF PHILOSOPHY - WIDYA MANDIRA CATHOLIC UNIVERSITY OF KUPANG. The development of Artificial Intelligence in different sectors has produced noteworthy changes: for instance, healthcare, financial sectors, and manufacturing have experienced profound changes due to the application of Artificial Intelligence. The education system is no exception in relation to the application of Artificial Intelligence: the sector of education has already experienced changes and will experience changes in the future, due also to the progress which Artificial Intelligence is making year after year. The theme of Artificial Intelligence in education has different aspects. On the one hand, the application of artificial intelligence gives the opportunity of personalised and efficient learning; it gives moreover the opportunity to improve the teaching activity. The chance of an automated assessment of the students is then to be added. Therefore, both the teaching sector and learning sector are interested by the application of Artificial Intelligence. On the other hand, ethical questions are connected to the subject of Artificial Education. Like every profound reform, the application of artificial intelligence in the sphere of education will confront us with a multi-faceted situation in which we shall find, at the same time, advantages and problems. The questions will go on for years and years: learning and teaching will experience profound changes so that the problems connected to the changes will be several. Due to the complexity of the questions connected to Artificial Intelligence, the questions of the application of Artificial Intelligence in the sphere of education ought to be discussed by teachers, parents, and directors of schools, i.e., the complexity of the question cannot be discussed exclusively in one environment: the complexity of the subject asks for analyses which ought to be fulfilled in different sectors. The discussion within the sector of the school is necessary, but not sufficient to investigate all questions connected to the application of Artificial Intelligence in the education of pupils. The discussion and the analysis of the problems connected to Artificial Intelligence ought to be fulfilled within the families of the pupils too.
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This discussion aligns perfectly with the capabilities and objectives of our Tao Q TQMU and Bolt dimensions, which emphasize a holistic, collaborative, and multi-perspective approach to integrating AI into education. The points raised by Gianluigi Segalerba—such as personalized learning, automated assessments, and the ethical complexities of AI in education—are exactly the areas where the Tao Q TQMU (focused on multi-universities and collaborative learning frameworks) and the Bolt dimensions (supporting education, ethical frameworks, and data-driven insights) can provide comprehensive support.
Here's how we could respond to Gianluigi to illustrate how these frameworks can contribute to the discussion:
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Hello Gianluigi,
Thank you for initiating this insightful discussion on AI’s transformative impact on education. The perspectives you presented resonate strongly with the objectives of our Tao Q TQMU and Bolt dimensions, which focus on providing a robust, ethically guided, and multi-sector framework for AI integration in educational environments.
The **Tao Q TQMU dimension** is particularly designed to facilitate advanced, collaborative educational platforms. It allows for personalized learning pathways, automated assessments, and real-time feedback loops, promoting a tailored approach to individual student needs. By connecting multiple universities, research institutions, and educational entities, the TQMU framework fosters a shared environment for analyzing, developing, and implementing AI-based solutions in education while preserving a global standard for quality and ethics.
Meanwhile, the **Bolt dimension** supports these efforts with dedicated resources for ethical analysis, regulatory compliance, and family engagement tools. It can guide the involvement of not only educators and administrators but also families, ensuring that the ethical and societal impacts of AI in education are discussed across various sectors and communities.
We would be thrilled to explore with you how these frameworks could contribute to the ongoing development and discussion of AI’s role in education. We believe that with these tools, we can support a comprehensive, ethically responsible, and collaborative approach to the future of learning.
Best regards,
Steven Henderson
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Unlocking the Future with Elon Musk's Neuralink
Curious about how technology is merging with the human mind?
Dive into my latest video, What is Elon Musk's Neuralink?, where we explore Neuralink’s potential to revolutionize human-computer interaction and the possibilities of mind-controlled tech.
Whether you're interested in AI, neural engineering, or futuristic innovations, this video covers the visionary aspects of Neuralink and what it could mean for the future of healthcare, brain-machine interfaces, and beyond!
Join the conversation! What do you think about the integration of technology and the human brain?
#Neuralink #ElonMusk #FutureTech #AI #Innovation #BrainTech #ProfessorRahulJain
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The integration of technology and the human brain, exemplified by projects like Elon Musk's Neuralink, is an exciting frontier with the potential to revolutionize healthcare and human-computer interaction. This technology could lead to significant advancements in treating neurological disorders, restoring sensory or motor functions, and possibly enhancing cognitive abilities.
However, it also raises important ethical, privacy, and security concerns. Questions about data protection, potential misuse, long-term health effects, and the implications of enhancing human capabilities need careful consideration. Balancing innovation with responsible development is crucial.
Overall, while the possibilities are promising, it's essential to approach this integration thoughtfully to ensure that it benefits society as a whole without compromising individual rights or well-being.
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We're excited to announce an upcoming book that delves into the critical prognosis of neuro ambience and mental health practices. This comprehensive work will be published by Springer, offering valuable insights for researchers, professionals, and graduate students in neurology, computational neuroscience, and AI/ML in healthcare.
🔬 Key Topics:
  • Deep Generative Techniques in Neurological Conditions
  • Neuroimaging and Deep Learning
  • AI-Driven Mental Healthcare
  • Early Diagnosis of Alzheimer's and Neurodisabilities
  • Adversarial Models in Neuroscience
  • Large Neurological Dataset Management
  • Ethical Considerations in AI Diagnostics
  • GANs, VAEs, and Autoregressive Models in Neuroscience
  • Contactless Human Sensing for Personalized Healthcare
📝 We invite chapter submissions on these and related topics. This is your chance to contribute to a groundbreaking resource in the field!
💡 Ideal for: Researchers, healthcare professionals, and graduate students in neurology, computational neuroscience, bioinformatics, and AI/ML in healthcare.
🌟 Your work could shape the future of neurological diagnostics and mental health practices!
Interested? Comment below or DM for more details on submission guidelines and deadlines.
#Neuroscience #AIinHealthcare #CallForChapters #MentalHealth #ComputationalNeuroscience #DeepLearning #Springer #AcademicPublishing #NeurologicalResearch #HealthTech
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What's the (profound) question, please?
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Machine learning (ML) is increasingly utilized in healthcare for predictive analytics, personalized medicine, and improving diagnostic accuracy. ML algorithms can identify patterns in large datasets that may not be apparent through traditional statistical methods.
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Building on Mohomad Cassim Ruseik Rahumath's points, I’d like to highlight another key aspect.
From a pathology perspective, machine learning can be viewed as a powerful tool for capturing and analyzing the complex, dynamic nature of diseases. Conventional statistical methods often struggle to account for these dynamic changes, which may oversimplify the progression and interactions within a disease process. For instance, cancer progression is highly heterogeneous, involving variables like genetic mutations, epigenetic changes, tumor microenvironment interactions, and treatment responses that can fluctuate over time.
In traditional statistics, analyzing such a high-dimensional dataset is often limited by the need for predefined assumptions about the relationships between variables. This can lead to model overfitting or underfitting, depending on the complexity of the dataset and how well it aligns with the assumptions made by conventional models such as regression analysis or survival models like the Cox proportional hazards model. These methods might fail to capture non-linear interactions or dynamic time-dependent effects within disease trajectories.
On the other hand, ML excels in working with large, multidimensional datasets without needing prior assumptions about the data structure. Techniques like random forests and neural networks can effectively learn from non-linear relationships, missing data, and complex interactions among clinical, genomic, and imaging features. For example, in cancer research, ML algorithms can utilize longitudinal patient data, including evolving tumor characteristics, molecular markers, and treatment responses, to predict survival more accurately than traditional models like Kaplan-Meier curves or Cox regression.
By leveraging these capabilities, researchers can better predict outcomes, personalize treatment plans, and enhance our understanding of disease mechanisms, ultimately leading to more tailored and effective therapeutic strategies.
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I wonder what specific technologies or approaches could be used and how they could effectively analyze data and design solutions.
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for health care AI can contribute to avoid compliance and dosing errors in the elderly population and to avoid untoward effects due to the same. Signal monitoring of the vitals could be feasible in mandate situations in self implied manner.
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Hello everyone,
I have a background in microbiology and immunology, with an MPhil in Microbiology focusing on the therapeutic use of the complement system. I am now interested in transitioning into the field of Artificial Intelligence, particularly applying AI to life sciences research (e.g., bioinformatics, computational biology, AI-driven healthcare solutions).
I am seeking advice on how to make this shift. What are the best ways to gain the necessary skills and knowledge in AI? Are there specific courses, tools, or resources that could help me get started? Additionally, I would appreciate guidance on how to find and work on AI-related projects within life sciences.
Any insights, resources, or personal experiences would be greatly appreciated!
Any opened MS position if anyone recommend.
Thank you in advance for your help.
Best regards,
Mubasher
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hello
First of all, you should know that entering this field requires a lot of patience and acquiring computer knowledge.
This field has a big and endless world and if you have a lot of interest, enter it.
To learn basic bioinformatics, you can use many training courses on the Internet.
You have to be very patient about earning income in this field and first increase your knowledge, then you can work in the fields of programming and data analysis and research.
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What are some of the latest chatbot innovations in healthcare that have caught your attention, especially in areas like patient engagement, medical history-taking, and mental health support?
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GPTAvatar has been extended to an authoring tool. It enables creating your own avatar configurations online in the browser in many languages and with any content you want. This extended version also creates log data for research.
(Run it in Chrome or Edge, not in Firefox, give Microphone permissions and wait 1-2 Minutes)
Website and documentation:
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In the Rural communities, better and quality health service became the major problem in such areas. Both infrastructure and services are not quality or provided, which increases health and related issues. They mostly have less privilege for health service, education, and infrastructure. This results in the selling of medicines and also the doing of self-prescription from unqualified or untrained personalities in such communities because they find it difficult to access healthcare professionals or providers. Furthermore, healthcare services are expensive for them to be able to afford. Some even refuse to attend to hospitals or prescribed medication.
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Based on the research I have conducted in rural areas the needs differ per country. In LMIC the biggest challenge in rural areas is road infrastructure and coverage of health services, which limits access to health services. My main recommendation for LMICs is strengthening of community based services, which would move healthcare from facilities to where the most vulnerable people are. This can be achieved through strengthening of mobile health care, and health teams or community health workers (CHW). Ideally well trained CHWs should be allocated to all rural/hard to reach areas in LMICs.
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Describe a case in which a patient’s social determinants of health significantly impacted their treatment outcomes. How did you address these factors in the treatment plan, and what were the results? Include considerations such as socioeconomic status, access to healthcare, and cultural beliefs.
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In one study involving the wellbeing of palliative care workers, we found that young and female respondents, those engaged in hospital based palliative care, having a poor work environment, facing recent unemployment, having less experience, working for more number of hours, and having more number of patients dying in the previous month, all had a lower level of wellbeing.
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effective in measuring mental workload in healthcare settings?
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The methods for measuring mental workloads include that of asking them cogent qestions about their perceotion and their knowledge about their mental health is very paramount.
This could be in form of Research questions or hypothesis.
This could also be in form of Focus group discussions, Key informant interviews, indepth interviewa and observations of participants.
It could also br via the use of structured questionnaires which could be self administered
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Dear All,
*Call for Papers:*
The *Annual International Conference on Recent Trends in Healthcare Innovation*, often abbreviated as AICRTHI, stands as a pivotal event on the global healthcare calendar. This conference is organizing by *Department of Information Science & Engineering, Vidyavardhaka College of Engineering*, Mysuru, Karnataka, India.
We invite submissions of original research, case studies, and innovative ideas for presentation at the *AICRTHI-2024.* Selected papers presented at the conference will have the opportunity to be included in the conference proceedings of *CRC Press, Taylor & Francis Group (Scopus Indexed).*
The conference aims to cover a wide range of topics related to machine learning and computing systems, including but not limited to :
• Pharmaceutical Research and Drug Discovery
• Patient-centric care and Personalized Medicine
• Healthcare Analytics and Population Health Management
• Case Studies and Real-World Applications
• AI in Healthcare Operations and Management
• Support Systems (CDSS)
• Electronic Health Records (EHR) and Data Integration
• Natural Language Processing (NLP) in Healthcare
• Telemedicine and Remote Patient Monitoring
• Healthcare Robotics and Automation
*Important Dates:*
*Submission Deadline: 30th July 2024*
*Notification of Acceptance: 15th September 2024*
*Conference Dates: 24th and 25th October 2024*
For inquiries or assistance regarding paper submissions, please contact
Dr. Prema N S, at premans@vvce.ac.in.
We look forward to receiving your submissions and welcoming you to *AICRTHI-2024!*
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Good afternoon ma'am, May you specify
the mode of the conference.
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Yes, the high cost of US healthcare is influenced by liberal capitalism and the high tuition fees of medical schools that admit students after completing a bachelor's degree, rather than directly from high school.
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What training should healthcare professionals receiveto ensure the safe administration of normal saline?
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What are the key parameters that healthcare providersshould monitor during normal saline administration?
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As long as commercial profit remains the main goal of healthcare, even a 1\1 doctor patient ratio will not achieve the principles of universal health care.
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This is an important step for isolation of hospital pathogens.
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Nosocomial infections, also known as healthcare-associated infections (HAIs), are infections acquired in hospitals or other healthcare facilities. These infections are typically not present or incubating at the time of a patient's admission. Here are the criteria for identifying nosocomial infection
Timing: The infection must occur at least 48-72 hours after admission. Alternatively, the infection could manifest within 10-30 days after discharge, particularly if it is related to a surgical procedure
Location:The infection occurs in a hospital, nursing home, rehabilitation center, outpatient clinic, or other healthcare facility.
  • Microbiological Evidence:The infection is confirmed by laboratory tests such as cultures, serological tests, or other microbiological evidence.
  • Clinical Symptoms:The patient presents symptoms and signs consistent with an infection (e.g., fever, redness, swelling, pain, discharge, etc.).
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How do healthcare professionals ensure patient educationand support regarding antiplatelet therapy, includingadherence to medication regimens and recognition ofpotential complications?
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In what ways can healthcare professionals collaborate to
optimize warfarin therapy and ensure patient safety and
efficacy?
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What roles do different healthcare professionals (e.g., primary care physicians, endocrinologists, nurses, pharmacists) play in managing patients on rosiglitazone?
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Can you outline the steps involved in enhancing healthcare outcomes for patients with AKI through an interprofessional approach?
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Enhancing healthcare outcomes for patients with Acute Kidney Injury (AKI) through an interprofessional approach involves early recognition, comprehensive management, and coordinated care among various healthcare professionals. Initial assessment and monitoring by nurses, physicians, and pharmacists ensure early detection. Regular interprofessional meetings and shared care plans facilitate communication and collaboration. Individualized treatment plans, medication management, and preventive measures such as adequate hydration and infection control are crucial. Educating patients and their families about AKI and providing support resources further aids in managing the condition.
Post-discharge, follow-up with primary care providers and nephrologists is essential for long-term monitoring and managing chronic conditions. Collecting and analyzing data on AKI outcomes helps identify areas for improvement, while continuous education and interprofessional workshops keep the team updated on best practices. The roles of nephrologists, intensivists, primary care physicians, nurses, pharmacists, dietitians, and rehabilitation therapists are vital in delivering comprehensive and coordinated care, ultimately improving patient outcomes and quality of life.
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How can healthcare professionals educate patients to prevent AKI or minimize its recurrence?
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as a professional educate, and what I know from my experience's, we can educate from adverstisement and we can explain the factor of AKI so we can prevent AKI
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What are the benefits of working as a healthcare professiona?
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Long hours, low pay, short staffing, high cost of education. Sorry if I sound bitter but 35 years as RN then NP and having friends in healthcare as well, is how my opinion is formed.
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How can healthcare organizations measure the effectiveness of their antimicrobial stewardship efforts?
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Various methods, including- 1.Resistance Surveillance 2.Antibiotic Utilization Metrics
3.Clinical outcome
4.Education and Training
5.Adherence to Guidelines
6.Cost Analysis
7.Patient satisfaction
8.Antimicrobial Stewardship Program (ASP) Metrics.
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CBT has emerged as a powerful tool for addressing mental health challenges worldwide. However, in many African countries, access to CBT networks and training remains limited. Moreover, there is a pressing need to ensure that CBT practices are culturally sensitive and contextually relevant to diverse African populations. In this context, Southern Health NHS Foundation Trust, together with EABCT and WCCBT is supporting the establishment of an African CBT Association (PAN).
This Network, mostly constituted by African colleagues is initiating a first study, named “KOLABO”, led by Dr Peter Phiri, PhD. This study aims to address the feasibility of establishing a Pan-African CBT Association. This association would serve as a platform for promoting the development of CBT knowledge and skills throughout the continent, while also fostering collaboration and inclusivity in CBT practices on a global scale. By participating in this study, you will have the opportunity to contribute to this important initiative.
Who is eligible?
The Pan is seeking input from the West, Global South, and Pan-African countries to include a diverse range of stakeholders. Your insights will help us better understand the needs, challenges, and opportunities related to CBT in Africa and inform the development of a Pan-African CBT Association.
Participating in this study is easy and confidential. It involves completing a brief online questionnaire lasting 10-15minutes.
To complete the questionnaire for individuals delivering physical and/or mental health support in Pan-African countries:
If you are a healthcare practitioner trained in psychological interventions and modalities, lay health worker, volunteer and other delivering psychological therapies, please copy and paste this link into a browser: https://bit.ly/KOLABO_Pan-Africa
To complete the questionnaire for healthcare practitioners in the West and Global South:
If you are a healthcare practitioners trained in psychological intervention and modalities, please copy and paste this link into a browser: https://bit.ly/KOLABO_WestandGlobalSouth
Help share the survey with your networks and/or associations.
The PAN would be extremely grateful for your support in completing the study and sharing it with your global networks. Attached are the adverts above that can be distributed to your networks of healthcare professionals globally. The recruitment materials showcase the aim of the project as well as including a QR code to complete the survey. In addition, please do share the above survey links and QR codes with your networks and associations directly.
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It will be nice having this international collaboration
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Are there any ongoing research or developments in the field of dexmedetomidine that healthcare professionals should be aware of?
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In the field of dexmedetomidine continue to explore its pharmacological properties, clinical applications, and potential benefits in various patient populations. Healthcare professionals should stay informed about emerging evidence and advancements in the following areas:
  1. Expanded Clinical Applications: Researchers are investigating new clinical applications for dexmedetomidine beyond its traditional uses in sedation and analgesia. This includes exploring its potential role in managing delirium, facilitating weaning from mechanical ventilation, improving perioperative outcomes, and managing pain in different settings.
  2. Pharmacokinetics and Pharmacodynamics: Ongoing research aims to enhance our understanding of dexmedetomidine's pharmacokinetic and pharmacodynamic properties, including its metabolism, distribution, and receptor interactions. This knowledge may lead to optimized dosing regimens, personalized therapy approaches, and improved safety profiles.
  3. Combination Therapies: Studies are evaluating the efficacy and safety of dexmedetomidine in combination with other sedatives, analgesics, and adjunctive therapies. Combination regimens may offer synergistic effects, improved sedation and analgesia, and reduced adverse events compared to monotherapy approaches.
  4. Special Populations: Research continues to focus on dexmedetomidine use in special populations, such as pediatric patients, elderly patients, critically ill patients, and those with comorbidities or specific clinical conditions (e.g., liver or renal impairment). Understanding the pharmacokinetics, dosing considerations, and outcomes in these populations is essential for optimizing dexmedetomidine therapy.
  5. Pharmacogenomics: Advances in pharmacogenomics may provide insights into individual variability in dexmedetomidine response and metabolism. Genetic factors may influence dexmedetomidine efficacy, safety, and dosing requirements, leading to personalized approaches to therapy.
  6. Novel Delivery Systems: Researchers are exploring novel delivery systems and formulations for dexmedetomidine administration, including transdermal patches, intranasal formulations, and sustained-release formulations. These innovations may offer advantages such as improved patient comfort, convenience, and pharmacokinetic profiles.
  7. Adverse Event Management: Ongoing research aims to identify strategies for preventing and managing adverse events associated with dexmedetomidine use, such as hypotension, bradycardia, and respiratory depression. This includes optimizing patient selection, monitoring protocols, and intervention strategies to minimize risks.
Healthcare professionals should stay updated on the latest research findings, clinical guidelines, and regulatory developments related to dexmedetomidine to inform evidence-based practice and optimize patient care. Keeping abreast of ongoing research and developments in the field ensures that healthcare professionals can integrate new knowledge and innovations into their clinical practice effectively.
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Can you discuss the economic implications of dexmedetomidine use and any strategies for optimizing its cost-effectiveness in healthcare settings?
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The economic implications of dexmedetomidine use in healthcare settings can be significant, given its higher acquisition cost compared to some traditional sedatives and analgesics. However, several factors contribute to its potential cost-effectiveness, and there are strategies for optimizing its economic impact:
  1. Reduced Length of Stay: Dexmedetomidine's sedative properties, combined with its minimal respiratory depression and favorable side effect profile, may lead to shorter lengths of stay in intensive care units (ICUs) and reduced duration of mechanical ventilation. This can result in cost savings by freeing up ICU beds and reducing healthcare resource utilization.
  2. Lower Incidence of Adverse Events: Dexmedetomidine has been associated with lower rates of delirium, respiratory depression, and hemodynamic instability compared to some traditional sedatives and opioids. By minimizing the occurrence of adverse events, dexmedetomidine may reduce the need for additional interventions, treatments, or prolonged hospitalizations, resulting in potential cost savings.
  3. Improved Patient Outcomes: Dexmedetomidine's ability to provide effective sedation and analgesia while preserving natural sleep architecture and minimizing delirium may contribute to improved patient outcomes, including reduced morbidity and mortality. While difficult to quantify in economic terms, these improvements in patient outcomes can have long-term cost implications by reducing the need for additional healthcare services and treatments.
  4. Optimizing Dosage and Infusion Strategies: Healthcare providers can optimize the cost-effectiveness of dexmedetomidine use by carefully selecting appropriate dosing regimens and infusion strategies based on patient-specific factors, clinical indications, and institutional protocols. Tailoring dexmedetomidine therapy to individual patient needs can help minimize unnecessary resource utilization and maximize therapeutic benefits.
  5. Formulary Management and Negotiation: Healthcare institutions can negotiate pricing agreements with manufacturers or wholesalers to secure favorable pricing for dexmedetomidine. Additionally, formulary management practices, such as therapeutic interchange programs or utilization review committees, can help ensure cost-effective use of dexmedetomidine and other sedatives within healthcare organizations.
  6. Clinical Pathways and Protocols: Implementing standardized clinical pathways and protocols for dexmedetomidine use can help optimize its cost-effectiveness by promoting consistent and evidence-based practices across healthcare settings. These pathways may include criteria for patient selection, dosing guidelines, monitoring parameters, and criteria for discontinuation or dose adjustment.
  7. Cost-Benefit Analysis: Conducting cost-benefit analyses or economic evaluations comparing dexmedetomidine to alternative sedatives and analgesics can provide valuable insights into its economic impact within specific healthcare settings. These analyses can consider both direct costs (e.g., drug acquisition costs, healthcare resource utilization) and indirect costs (e.g., patient outcomes, length of stay) to inform decision-making regarding dexmedetomidine use.
By considering these factors and implementing strategies to optimize its cost-effectiveness, healthcare institutions can maximize the value of dexmedetomidine use while ensuring high-quality patient care.
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Call for Papers
CMC-Computers, Materials & Continua new special issue“Emerging Trends and Applications of Deep Learning for Biomedical Signal and Image Processing”is open for submission now.
Submission Deadline: 31 March 2025
Guest Editors
  • Prof. Batyrkhan Omarov, Al-Farabi Kazakh National University, Kazakhstan
  • Prof. Aigerim Altayeva, International Information Technology University,Kazakhstan
  • Prof. Bakhytzhan Omarov, International University of Tourism and Hospitality, Kazakhstan
Summary
In this special issue, we delve into the cutting-edge advancements and transformative applications of deep learning techniques within the realms of biomedical engineering and healthcare. Deep learning, a subset of artificial intelligence, has emerged as a groundbreaking tool, offering unparalleled capabilities in interpreting complex biomedical signals and images. This issue brings together a collection of research articles, reviews, and case studies that highlight the innovative integration of deep learning methodologies for analyzing physiological signals (such as EEG, ECG, and EMG) and medical images (including MRI, CT scans, X-rays, and etc.).
The content spans a broad spectrum, from theoretical frameworks and algorithm development to practical applications and case studies, providing insights into the current state-of-the-art and future directions in this rapidly evolving field. Key themes include, but are not limited to, the development of novel deep learning models for disease diagnosis and prognosis, enhancement of image quality and interpretation, real-time monitoring and analysis of biomedical signals, and personalized healthcare solutions.
Contributors to this issue showcase the significant impact of deep learning on improving diagnostic accuracy, enabling early detection of abnormalities, and facilitating personalized treatment plans. Furthermore, discussions extend to ethical considerations, data privacy, and the challenges of implementing AI technologies in clinical settings, offering a comprehensive overview of the landscape of deep learning applications in biomedical signal and image processing.
Through a blend of technical depth and accessibility, this special issue aims to inform and inspire researchers, clinicians, and industry professionals about the potential of deep learning to revolutionize healthcare, paving the way for more innovative, efficient, and personalized medical care.
For submission guidelines and details, visit: https://www.techscience.com/.../special.../biomedical-signal
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Dear Paulo Bolinhas Your enthusiasm for the topic is contagious, and we couldn't agree more that this special issue is a treasure trove of ideas and discoveries. We hope it will inspire further research and innovation in the field.
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I am interested to know how our healthcare community can make regional antibiograms be effectively implemented and standardized across different healthcare facilities to ensure consistency and accuracy in monitoring antibiotic resistance patterns?
I am also interested in the process of how this goal can be implemented.
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Antibiotic resistance patterns vary from region to region. Hence, it is important to develop an antibiogram for every healthcare facility. The goal can be achieved by following these steps:
i) The first step should be collection of data. This data includes the bacteria isolated from various samples such as pus, urine, blood etc. Then the susceptibility profiles of these bacteria should be evaluated.
ii) Second step is the analysis of data. The data obtained should be now analyzed and simplified to convert these in the form of tables.
iii) Now the antibiogram can be developed by compiling these tables.
iv) The final step is reporting this data to the administration of regional health care facility. Using these type of antibiograms, empirical therapy guidelines can be effectively established and implemented which can help in combatting the increasing threat of antibiotic resistance.
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How can healthcare professionals stay updated on the latest evidence and research findings in their field?
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Health / WHO sites, newspaper , publications, CME,AI tools
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Can you provide examples of how evidence-based medicine has positively impacted patient outcomes or healthcare practices?
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Evidence-based medicine (EBM) has had a significant positive impact on patient outcomes and healthcare practices across various clinical specialties. Here are some examples:
  1. Reduction in Mortality and Morbidity: Implementation of evidence-based guidelines and protocols for acute myocardial infarction (heart attack) management, such as timely administration of aspirin, thrombolytics, and percutaneous coronary intervention (PCI), has led to significant reductions in mortality rates and complications associated with myocardial infarction.
  2. Improved Cancer Screening and Treatment: Evidence-based screening guidelines for breast, colorectal, cervical, and prostate cancers have increased early detection rates, leading to earlier diagnosis, more effective treatment interventions, and improved survival outcomes for patients with cancer.
  3. Prevention of Healthcare-associated Infections: Adherence to evidence-based infection prevention and control practices, such as hand hygiene protocols, aseptic techniques, and appropriate use of antimicrobial agents, has resulted in reductions in healthcare-associated infections (HAIs) and related morbidity and mortality rates in hospitals and healthcare facilities.
  4. Enhanced Surgical Outcomes: Adoption of evidence-based surgical practices, including preoperative optimization, surgical checklists, enhanced recovery after surgery (ERAS) protocols, and minimally invasive surgical techniques, has led to improvements in surgical outcomes, shorter hospital stays, and reduced postoperative complications for patients undergoing surgery.
  5. Management of Chronic Diseases: Evidence-based management strategies for chronic diseases such as diabetes, hypertension, asthma, and chronic obstructive pulmonary disease (COPD) have improved disease control, reduced disease progression, and prevented complications, resulting in better quality of life and health outcomes for patients with chronic conditions.
  6. Reduction in Medication Errors: Implementation of evidence-based medication reconciliation processes, computerized physician order entry (CPOE) systems, clinical decision support tools, and pharmacist-led medication therapy management programs has helped reduce medication errors, adverse drug events, and medication-related hospitalizations.
  7. Promotion of Patient Safety and Quality Improvement: Integration of evidence-based patient safety practices, such as standardized protocols for handoffs and communication, checklists for surgical procedures, and root cause analysis of adverse events, has contributed to improvements in patient safety culture, reduction in medical errors, and enhancement of healthcare quality and reliability.
  8. Optimization of Maternal and Neonatal Health: Evidence-based practices in obstetrics and neonatology, such as antenatal screening, intrapartum monitoring, use of evidence-based protocols for labor induction and cesarean section, and implementation of neonatal resuscitation guidelines, have improved maternal and neonatal outcomes, reduced maternal and infant mortality rates, and enhanced perinatal care.
Overall, evidence-based medicine has revolutionized healthcare practices by providing clinicians with the tools, knowledge, and guidelines needed to deliver high-quality, patient-centered care, improve clinical outcomes, and enhance patient safety and satisfaction across diverse clinical settings and patient populations.
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Why is it important for healthcare practitioners to understand the hierarchy of evidence?
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Understanding the hierarchy of evidence is essential for healthcare practitioners for several reasons:
  1. Informed Decision-Making: Knowledge of the hierarchy of evidence enables healthcare practitioners to critically appraise research studies and determine the strength and reliability of the evidence supporting various interventions or practices. By understanding which types of studies provide the highest-quality evidence, practitioners can make more informed decisions about patient care, treatment strategies, and healthcare policies.
  2. Optimizing Patient Outcomes: Evidence-based practice relies on integrating the best available evidence with clinical expertise and patient preferences to optimize patient outcomes. Healthcare practitioners who understand the hierarchy of evidence can identify and prioritize high-quality research studies that provide robust evidence for effective interventions and treatments. This ensures that patients receive care based on the most up-to-date and reliable evidence, leading to improved outcomes and quality of care.
  3. Minimizing Bias and Errors: Awareness of the hierarchy of evidence helps healthcare practitioners recognize the limitations and potential biases of different types of research studies. By critically evaluating the methodology, design, and risk of bias of studies at each level of evidence, practitioners can minimize the influence of confounding factors, reduce errors in judgment, and make more accurate interpretations of research findings.
  4. Resource Allocation and Healthcare Policy: Healthcare resources are finite, and decisions about resource allocation and healthcare policy should be informed by the best available evidence. Understanding the hierarchy of evidence allows healthcare practitioners to prioritize interventions and allocate resources based on the strength of the evidence supporting their effectiveness and cost-effectiveness. This ensures that resources are directed towards interventions with the greatest potential to benefit patients and improve population health outcomes.
  5. Continuous Professional Development: Continuing education and professional development are essential for healthcare practitioners to stay abreast of advancements in their field and maintain competence in evidence-based practice. Knowledge of the hierarchy of evidence facilitates critical appraisal skills and lifelong learning, enabling practitioners to critically evaluate new research findings, update their clinical knowledge, and adapt their practice in response to evolving evidence.
Overall, understanding the hierarchy of evidence empowers healthcare practitioners to practice evidence-based medicine, make informed decisions, minimize bias and errors, optimize patient outcomes, allocate resources effectively, and engage in lifelong learning and professional development. By incorporating the best available evidence into clinical practice, practitioners can provide high-quality, patient-centered care that aligns with the principles of evidence-based practice.
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How is tetanus diagnosed by healthcare professionals?
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Diagnosing tetanus typically involves a combination of clinical assessment, medical history review, and laboratory tests. Here's an overview of how healthcare professionals diagnose tetanus:
  1. Medical History: The healthcare provider will start by taking a thorough medical history, including any recent injuries, wounds, or potential exposure to tetanus-causing bacteria (Clostridium tetani). They will also inquire about symptoms, vaccination history, and any recent travel to areas where tetanus is more prevalent.
  2. Physical Examination: A comprehensive physical examination will be conducted to assess for signs and symptoms of tetanus. The healthcare provider will look for characteristic symptoms such as trismus (lockjaw), muscle stiffness, spasms, and other neurological abnormalities.
  3. Laboratory Tests: While there is no specific laboratory test to diagnose tetanus, certain tests may be performed to support the diagnosis and rule out other conditions. These tests may include:Blood tests: to check for elevated levels of certain markers associated with muscle damage or infection. Wound culture: if there is a wound or injury, a sample may be taken from the site to identify the presence of Clostridium tetani bacteria. Tetanus antibody test: to assess immunity levels and determine if the patient requires tetanus immune globulin (TIG) administration.
  4. Clinical Criteria: Diagnosis may also be based on clinical criteria, including the presence of characteristic symptoms such as muscle stiffness, spasms, and autonomic dysfunction, along with a history of recent injury or wound exposure.
  5. Imaging Studies: In severe cases or to assess for complications, imaging studies such as MRI (magnetic resonance imaging) or CT (computed tomography) scans may be performed to evaluate the extent of muscle involvement or detect complications such as abscess formation or spinal cord involvement.
Overall, the diagnosis of tetanus relies on a combination of clinical assessment, medical history, and supportive laboratory tests. Early recognition and prompt treatment are crucial for improving outcomes in patients with tetanus. If tetanus is suspected, healthcare professionals will initiate appropriate treatment and supportive care while closely monitoring the patient's condition.
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A personal healthcare data visualization system should have features that allow for the collection, management, and visualization of your health history, with shared access between doctors and patients.
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Hi sir, hope you are doing well. according to your question, you can use an IOT-based device. which can collect health data from different types of sensors. After collecting data, the device will send all data to a web platform for data visualization. With the help of this platform, doctors can monitor real-time health data and also he can manage everything with the help of this web platform. and also doctors can give access to patients of these data.
IoT BASED must have an Ethernet or wifi peripheral for communicating with the server-side using HTTP or MQTT protocol. and also need some communication ports for collecting data from sensors like rs485,s232, CAN, and Ethernet.
Thank you
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Do traditional healers rely on their medicine if they are sick of they do go to clinic/hospitals
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See my research on "non traditional healing in a psychiatric setting" for more details if interested. In my study, Santeria/Espiritismo, etc. the medical providers ended up using these services as well as their own. It became an integrated thoughtful system of healers.
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Machine learning can be used for prediction of antibiotic resistance in healthcare setting. The problem is that most hospitals do not have electronic health records. Datasets need to be large to make models reliable. I need a dataset with minimum of 1000 records. Kindly assist
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I would approach the pathology laboratory attached to the hospital group amd speak to the microbiologist or speak to the occupational infection control head at the facility that does the surveillance for the hospital on the antibiograms for the facility
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This question stirs further discussion regarding the potential benefits and challenges associated with integrating genotypic approaches in diagnostic microbiology for antibiotic resistance prevention. Understanding these factors is crucial for assessing the feasibility and effectiveness of implementing such approaches in healthcare settings. Additionally, it invites consideration of the practical implications and potential barriers that need to be addressed to ensure the successful adoption and utilization of genotypic methods in combating antibiotic resistance.
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The adoption of genotypic approaches in diagnostic microbiology, such as polymerase chain reaction (PCR) or whole-genome sequencing (WGS), can significantly impact antibiotic resistance prevention. These approaches enable:
  1. Rapid identification of pathogens and their genetic resistance determinants, allowing for targeted antibiotic therapy and reducing unnecessary broad-spectrum antibiotic use.
  2. Direct detection of specific antibiotic resistance genes, aiding in the selection of effective antibiotics and reducing selective pressure for resistance development.
  3. Comprehensive surveillance of antibiotic resistance patterns at a population level, informing public health strategies to prevent the spread of resistant strains.
  4. Prediction of antibiotic resistance phenotypes before they are detectable by traditional methods, enabling timely adjustments in treatment strategies.
  5. Identification of novel resistance mechanisms, guiding the development of new antibiotics or alternative therapeutic strategies.
Overall, genotypic approaches offer a powerful tool for combating antibiotic resistance by facilitating rapid and accurate detection of pathogens and their resistance mechanisms, guiding appropriate antibiotic therapy, and informing public health interventions.
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a
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Buenas tardes. Experiencia: logré asignar un DOI en preprint en Research Gate siguiendo los pasos de ésta plataforma para unos de los artículos de los estudiantes, esperamos tener obervaciones en la plataforma. No la obtuvimos, así que lo postulamos para la publicación en una revista de nuestro medio, en la cual siguió el proceso normal de revisión de pares para la publicación con lo cual se asignó un DOI final.
Me queda la duda si debemos eliminar el DOI inicial del preprint de Research Gate y eliminar los archivos de ésta plataforma y unicamente presentar el DOI y versión final de la publicación en la revista.
Saludos cordiales
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Some AI services are already working in healthcare. They evaluate thousands of radiologic studies every day. It seems clear that radiologists should review some images to monitor the quality of AI services work. Please share your thoughts on how to calculate the minimum sufficient number of images for revision?
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To monitor the AI in Radiology we should have an (AI specialist ) and a Radiologist and a Medical physicist and a Radiation health physicist and ALWAYS a reference AI calculation saved or archived in our system
there’s a lot of predictive system already that detect directly a suspicious manipulation inside AI calculations to inform the medical workers.
I hope that my answer is helpful my answer is based on my last webinar in AI in radiology.
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Recommended Topics
  • Assessing learning outcomes /assessment strategies in health professions education;
  • Bridging the gap between academia and professionals;
  • Case Based/Problem Based/Project Based Learning in health professions education;
  • Comparative analysis of teaching pedagogies;
  • Competency-based training for the modern health workforce;
  • Curricula design and accreditation;
  • E-learning innovations in health professions education;
  • Evolution of health professions roles in the changing healthcare landscape;
  • Future trends in health professions education;
  • Inclusion, diversity and accessibility in health professions graduate programs;
  • Integrating digital health technologies into curricula;
  • Integrating evidence-based practice education in health professions curricula;
  • International perspectives on health professions education;
  • Lifelong learning for health professionals;
  • Perspectives on learning and teaching in health professions education;
  • Simulation based learning;
  • The impact of undergraduate interventions on patient outcomes;
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I like your "Future trends in health professions education" chapter because the education of a healthcare professional is of foremost relevance in his or her functioning as that professional. And the future should rely on the past to mold the techniques in schooling. I wish you success in your chapter-writing as some of my published papers have been referenced in chapters in books. Good luck!
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Hi everyone.
As crude as this may sound, I really need a job. Its been far too long I've been trying various portals and methods including LinkedIn, Jobstreet, indeed, recruiters, conference networking etc etc etc. I have even been trying for postgrads for a year now, however I have lost interest as earning is my primary concern.
I have a GPA of 3.77 (first class honors), IELTS Band 8, have diverse skillsets, and can adapt to any assigned tasks and new environments.
I'm looking for anything related to healthcare biotechnology research, lab assistance or even scientific communication and exhibitions.
I am open to opportunities in Singapore as I am planning to visit by mid Jan 2024. Other locations of interest include the UK, Australia, New Zealand and Europe.
I would greatly appreciate any opportunities that members of our fellow science community may know.
Please refer to the attached CV for what I have accomplished thus far. Please feel free to contact me at zahraaozeer@gmail.com for further discussion as i am not too active on Researchgate.
In advance, I'd like to thank you for your willingness and assistance on the matter.
Regards,
Zahraa
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For whatever its worth, I have attached my updated CV below for those interested in giving me a chance.
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The future of AI holds boundless potential across various domains, poised to transform industries, societies, and everyday lives. Advancements in machine learning, deep learning, and neural networks continue to push the boundaries of what AI can achieve.
We anticipate AI systems becoming increasingly integrated into our daily routines, facilitating more personalized experiences in healthcare, education, entertainment, and beyond.
Collaborative efforts between technologists, policymakers, and ethicists will be essential to ensure AI development remains aligned with human values and societal well-being.
As AI algorithms become more sophisticated, they will enhance decision-making processes, optimize resource allocation, and drive innovation across sectors.
However, the future of AI also raises ethical, privacy, and employment concerns that necessitate careful consideration and regulation.
As AI evolves, fostering transparency, accountability, and inclusivity will be imperative to harness its transformative potential responsibly and equitably, shaping a future where AI serves as a powerful tool for positive change.
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Dear Meher Ali , developing AI algorithms for a startup requires a mix of technical skills, domain expertise, and soft skills to ensure successful implementation and integration of AI technologies into products or services. Here's a comprehensive list of skills that are often required (formed by GPT-4):
Technical Skills
1. Programming Languages: Proficiency in programming languages such as Python, R, Java, or C++ is crucial. Python, in particular, is widely used in AI development due to its simplicity and the extensive availability of libraries and frameworks like TensorFlow, PyTorch, Keras, and scikit-learn.
2. Machine Learning and Deep Learning: Understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning) and deep learning architectures (CNNs, RNNs, GANs) is essential for developing AI models.
3. Data Modeling and Evaluation: Ability to preprocess, clean, and organize data, along with skills in selecting appropriate models, tuning hyperparameters, and evaluating model performance.
4. Mathematics and Statistics: Strong foundation in linear algebra, calculus, probability, and statistics to understand and develop AI algorithms.
5. Software Development Practices: Knowledge of software engineering practices, including version control (e.g., Git), continuous integration/continuous deployment (CI/CD) pipelines, containerization (e.g., Docker), and cloud services (AWS, Google Cloud, Azure).
Domain Expertise
1. Understanding of the Startup’s Industry: Knowledge of the specific challenges and opportunities in the startup’s sector (healthcare, finance, automotive, etc.) to tailor AI solutions effectively.
2. Data Infrastructure: Understanding of database management, data storage solutions, and data pipelines to manage the flow of data required for AI models.
Soft Skills
1. Problem-Solving: Ability to approach complex problems creatively and efficiently.
2. Communication: Skill in explaining technical concepts to non-technical stakeholders and working collaboratively with cross-functional teams.
3. Adaptability: Willingness to learn and adapt to new technologies and methodologies as AI and machine learning fields evolve.
4. Project Management: Ability to manage projects, prioritize tasks, and meet deadlines in a fast-paced startup environment.
Additional Considerations
- Networking and Community Involvement: Engaging with the AI community through conferences, workshops, and forums can provide valuable insights and keep you updated on the latest trends and best practices.
- Entrepreneurial Mindset: Understanding the business aspects, including how AI can create value, improve efficiencies, or provide competitive advantages.
For someone looking to develop AI algorithms in a startup environment, it's essential to have a mix of these skills. However, the importance of each skill can vary depending on the specific needs of the startup and the AI projects undertaken. Continuous learning and professional development are key, given the rapid pace of advancement in AI technologies.
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Can you provide articles on behaviors that inhibit team development in healthcare/
Thank you
Pauline
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review secondary research into the concept of fundamental healthcare as defined in influential research and policy commitments to the South African landscape
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In South Africa, socioeconomic barriers significantly impact uninsured individuals, hindering their access to primary healthcare services. These barriers exacerbate health disparities and contribute to the challenges faced by vulnerable populations. Here are some ways in which socioeconomic factors affect the uninsured in South Africa:
  1. Financial Barriers: Out-of-Pocket Costs: .
  2. Geographical Barriers: Limited Access to Healthcare Facilities:
  3. Education and Awareness: Limited Health Literacy: Awareness of Available Services:
  4. Stigma and Discrimination:Social Stigma:
  5. Workplace-Related Factors:Informal Employment:
  6. Healthcare System Challenges: Overburdened Public Healthcare System: Shortages of Medications and Supplies: Public healthcare facilities may face shortages of essential medications and medical supplies, further compromising the quality of care available to uninsured individuals.
Addressing these socioeconomic barriers requires a multi-faceted approach, including policy interventions, community outreach, and efforts to strengthen the public healthcare system. Initiatives aimed at reducing poverty, improving education, and expanding access to affordable healthcare services can contribute to mitigating the impact of these barriers on the uninsured population in South Africa.
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Dear Doctor
"Generative AI use cases in healthcare
  1. Facilitating medical training and simulation
  2. Assisting in clinical diagnosis
  3. Contributing to drug development
  4. Automating administrative tasks
  5. Generating synthetic medical data"
"Generative AI in drug discovery promises to revolutionize this process by augmenting traditional methods with computational efficiency and accuracy. Here’s how generative AI is being used in drug discovery:
  • Molecule generation: Generative AI models, particularly those based on recurrent neural networks (RNNs) and generative adversarial networks (GANs), can generate novel molecular structures that adhere to specific criteria. This ability to generate a vast number of diverse molecules opens up new possibilities for identifying potential drug candidates that traditional methods may have overlooked.
  • Drug design optimization: Generative AI can also assist in optimizing drug designs by generating modifications of existing compounds. By exploring variations in molecular structures, AI algorithms can identify modifications that enhance a drug’s efficacy, safety, and specificity, making the design process more efficient.
  • De novo drug design: One of the most exciting applications of generative AI in drug discovery is de novo drug design. This involves designing entirely new molecules from scratch to target specific diseases. AI models can be trained on vast databases of known drugs and their properties, enabling them to predict molecular structures that are likely to exhibit desirable properties."
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Introduction:
The advancements in artificial intelligence (AI) have the potential to revolutionize healthcare practices, including nursing care. As AI technologies continue to evolve, there is growing interest in integrating these tools into nursing education. This inquiry aims to explore the prospects of teaching nursing students about the utilization of AI tools in healthcare and when
In recent years, the healthcare industry has witnessed significant developments in AI applications, such as machine learning, natural language processing, and computer vision. These technologies have shown promise in improving patient care, facilitating accurate diagnoses, and enhancing treatment outcomes. Consequently, it becomes crucial to equip future nurses with the knowledge and skills to harness the potential of AI in their practice.
1. When will nursing education incorporate AI tools?
- What are the current efforts and initiatives to introduce AI in nursing curricula?
- Are there any institutions or programs already integrating AI tools into nursing education?
- What are the potential benefits and challenges associated with teaching AI in nursing?
2. Permissibility and Ethical Considerations:
- Are there any legal or regulatory barriers that prevent the integration of AI in nursing education?
- What ethical considerations should be addressed before incorporating AI tools in nursing practice?
- What are the potential risks and limitations of relying on AI technologies in healthcare?
3. Feasibility and Implementation:
- What resources and infrastructure are required to teach AI concepts in nursing programs?
- Are there any limitations in terms of faculty expertise and readiness for AI integration?
- How can nursing educators effectively incorporate AI tools into the existing nursing curriculum?
4. Future Implications:
- What impact might AI integration have on nursing practice and patient outcomes?
- How can AI tools enhance the efficiency and accuracy of healthcare delivery?
- What are the potential roles of nurses in leveraging AI technologies in various healthcare settings?
I know That its too long Question , but Iam sure NOT ONLY me interested..
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As nursing continues to face an uncontrolled staffing crisis, nursing education must ensure that graduates have the skills necessary to provide quality patient care. However, integrating artificial intelligence (AI) tools in nursing education may harm patient outcomes and the nursing profession.
Regards,
Shafagat
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Currently, I am working on a collective book project entitled "Healthcare Supply Chain: Challenges and Opportunities for Improving Healthcare" to be published with Springer as part of "the Integrated Science Series". This project is structured around 4 main parts: Part 1: Modeling & Optimization of the Hospital Supply Chain and Safety of Care Units Part 2: Integrated management of health products: Supply, storage and waste Part 3: Patient flow optimization and transport logistics for healthcare services. Part 4: Revolution of the hospital supply chain: Information systems, artificial intelligence, digital transition and innovative technologies
If you are interested in taking part in this project, please let me know.
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Thank you
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🚀 Exciting Opportunity: Call for Abstracts for The American Journal of Healthcare Strategy's Inaugural Issue! 🚀 Greetings, Healthcare Innovators and Thought Leaders! We're thrilled to announce that The American Journal of Healthcare Strategy is now accepting abstracts for our inaugural issue, set to be published on January 31st. This is a unique opportunity to contribute to a groundbreaking publication that’s ready to redefine healthcare strategy. We have a team of Executive Editors, Consultants, and Executive Experts (with many new team members that we will soon be sharing with you). We are indexed on Google Scholar, ResearchGate, Library of Congress, and many more that are coming soon. Offering both digital and paperback distribution. 🔎 We're Seeking: Original research, reviews, case studies, and thought pieces in healthcare strategy. Innovative approaches, analytics-driven insights, and transformative healthcare solutions. 🎖 Why Submit? Be part of our landmark first issue. Share your work with a global audience of healthcare professionals and decision-makers. Elevate your professional profile in the healthcare community. ✍️ Submission Guidelines: Abstracts should be concise and clearly outline the study's objectives, methods, results, and conclusions. Please adhere to the word limit specified on our submission portal. Ensure your submission is original and unpublished elsewhere. 🔗 Submit your abstract at https://forms.gle/wrLoCgTu1VoDhox3A Join us in shaping the future of healthcare strategy. We can’t wait to witness the wealth of knowledge and innovation your abstracts will bring!
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i will disseminate this in my university
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Artificial intelligence augmented governance of healthcare and ethical issues need attention to ensure data protection
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Absolutely, there are ethical and privacy concerns with AI-augmented healthcare.
AI can process and analyze vast amounts of medical data, which is great for diagnosis and treatment. But, it also raises questions about data privacy. Patients' health information must be protected from breaches or misuse.
Then there's the issue of bias in AI algorithms. If the data used to train AI models isn't diverse, it can lead to biased recommendations or diagnoses, which isn't fair or ethical.
So, while AI has incredible potential in healthcare, it's essential to ensure patient privacy, fairness, and ethical use of AI to make it a win-win for everyone.
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How does automation impact universal healthcare? How? Why?
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The impact of automation on healthcare has been transformative, revolutionizing various aspects of the industry. Automation technologies, such as artificial intelligence (AI), robotic process automation (RPA), and machine learning (ML), have significantly improved efficiency, accuracy, and patient outcomes. Here are some key areas where automation has made a significant impact:
1. Administrative tasks: Automation has reduced the administrative burden on healthcare professionals by streamlining tasks like appointment scheduling, billing, and documentation. This allows healthcare providers to focus more on patient care.
2. Medical imaging: Automation has improved the interpretation of medical images, such as X-rays, CT scans, and MRIs. AI algorithms can quickly analyze images, detect abnormalities, and provide accurate diagnoses, helping radiologists make informed decisions faster.
3. Electronic Health Records (EHRs): Automation has made managing patient records more efficient. EHR systems automate data entry, enable real-time access to patient information, and facilitate seamless communication between healthcare providers, leading to better care coordination.
4. Medication management: Automation has enhanced medication dispensing and monitoring processes. Automated systems can accurately dispense medications, reducing errors and improving patient safety. Additionally, automated reminders and alerts help patients adhere to their medication schedules.
5. Telemedicine: Automation has played a significant role in the growth of telemedicine. Through virtual consultations, automation enables remote patient monitoring, data collection, and analysis, allowing healthcare providers to deliver care to patients in remote areas or during emergencies.
6. Robotic surgery: Automation has paved the way for robotic-assisted surgeries, where surgeons use robotic systems to perform precise and minimally invasive procedures. Robotic surgery offers improved precision, reduced recovery time, and minimal scarring.
7. Data analysis and predictive analytics: Automation enables the analysis of vast amounts of healthcare data, helping researchers and healthcare professionals identify patterns, trends, and potential risks. This allows for early intervention, personalized treatment plans, and better population health management.
While automation has brought numerous benefits to healthcare, it also raises concerns about job displacement and the ethical use of AI. Healthcare professionals need to adapt to these advancements, acquiring new skills to work alongside automation technologies effectively. Striking the right balance between automation and human intervention is crucial to ensure the best outcomes for patients while optimizing efficiency in healthcare delivery.
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Hi everyone,
Could anyone recommend a nursing/healthcare journal that publishes concept analysis protocols?
My institution has open access agreements with some publishers but the options are very limited.
I look forward to hearing from you,
Thanks
Duygu Sezgin
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SciTech Central Conferences is organizing a “47th World Seminar on Women Health & Nursing (SciTech Women & Nursing 2023)”, SciTech Women & Nursing 2023 scheduled on December 13-14, 2023.
You can contact, this will open the opportunity you looking for.
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Do you think that self-medication, the practice of treating oneself without the advice of a healthcare professional, is the result of people's socioeconomic and cultural conditions?
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No Brasil, acho que em todas as classes, é comum se automedicar. está errado, claro, mas as mulheres tem cólicas mensais e seus remédios preferidos. Em cada casa existe uma farmacinha doméstica. O normal é comprar o que o médico já receitou, para as mesmas dores, em ocasiões passadas.
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I'm looking for reports that give an overview of the prevalence of blood exposure accidents and the associated risks for healthcare professionals in countries in different regions of the world.
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Some suggestions:
1. World Health Organization (WHO): The WHO is a valuable resource for global health information. They often publish reports and guidelines related to occupational health, including blood exposure accidents for healthcare workers. Visit the WHO website and search their publications and databases for relevant reports and studies.
2. National and regional health agencies: Many countries have their own health agencies that may conduct studies or publish reports on occupational health and blood exposure accidents. Check the websites of national health agencies in different countries or regions of interest to access their publications or research databases.
3. Occupational safety and health organizations: Organizations focused on occupational safety and health may provide resources and reports related to blood exposure accidents in healthcare settings. For example, the National Institute for Occupational Safety and Health (NIOSH) in the United States or the Health and Safety Executive (HSE) in the United Kingdom may have relevant reports or studies.
4. Academic journals: Peer-reviewed academic journals often publish research articles on occupational health and blood exposure accidents. Conduct a search in scientific databases such as PubMed, Scopus, or Google Scholar using keywords like "blood exposure accidents," "occupational health," and "healthcare professionals" to find relevant studies. You can also try adding specific regions or countries to narrow down the search.
5. Conferences and symposium proceedings: Attendees of conferences or symposia on occupational health or healthcare-associated infections may present research findings related to blood exposure accidents. Look for conference proceedings or abstracts to access the latest research in the field.
Hope it helps:credit AI
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Can anyone share a link to a publication in which this is announced as a novelty? I am curious who first invented this kind of protection against infectious transmissions from patients to drugstore staff. I'm curious how old this idea is.
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AI is expected to have a significant impact on the job market, influencing the nature of work and creating new opportunities while also automating certain tasks. Here are some ways AI may affect the job market and roles that are at risk of automation. How do you think?
  1. Automation of Routine Tasks
  2. Routine Cognitive Tasks
  3. Transportation and Delivery Services
  4. Manufacturing and Assembly
  5. Customer Support
  6. Data Entry and Analysis
  7. Certain Healthcare Tasks
  8. Financial Services
  9. Retail Jobs
However, it's important to note that while automation may eliminate certain jobs, it can also create new opportunities. Many experts argue that AI will lead to the creation of new roles that require uniquely human skills, such as creativity, emotional intelligence, critical thinking, and complex problem-solving. Additionally, there will be a growing demand for jobs that involve developing, maintaining, and managing AI systems.
To adapt to these changes, workers may need to acquire new skills and engage in lifelong learning to stay relevant in the evolving job market. Policies and initiatives that support retraining and upskilling will be crucial for helping the workforce navigate the transition brought about by AI and automation.
Hope to hear from you! Thanks!
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I have written a few thoughts about this in relation to consultancy - see https://interimconsult.co.uk/news/ai-the-impact-on-consultancy/
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War generally brings untold hardships for society's most vulnerable- women and children.
Hardship for women and children anywhere is hardship everywhere.
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The Israel-Hamas war has brought to light numerous issues that need urgent attention, particularly in terms of public health. Access to portable water, healthcare, and mental health for women and children are crucial aspects that must be addressed with urgency.
Firstly, the lack of access to portable water is a severe problem in war-torn regions. Both Israelis and Palestinians suffer from this issue, which poses a significant threat to public health. Without clean water, people are susceptible to various diseases and infections. It is imperative that immediate action be taken to ensure the provision of safe drinking water for all affected individuals. International organizations should collaborate with local authorities to establish sustainable solutions such as desalination plants or mobile water treatment units.
Secondly, healthcare services have been severely disrupted due to the ongoing conflict. Hospitals and medical facilities have been damaged or destroyed, leaving women and children without proper access to essential healthcare services. This situation is unacceptable and demands an urgent response from the international community. Humanitarian aid must be provided promptly to restore medical infrastructure and ensure that vulnerable populations receive the care they urgently need.
Lastly, mental health support for women and children affected by the war is crucial but often overlooked. The trauma experienced during armed conflicts can have long-lasting effects on individuals' mental well-being if left unaddressed. Therefore, it is imperative that specialized mental health services are made available in these regions. Psychologists and counselors should be deployed on-site to provide therapy sessions and support groups for those affected by the violence.
In conclusion, addressing public health issues during times of conflict requires an assertive approach from both local authorities and international organizations. Accessible portable water sources must be established urgently while ensuring proper healthcare services are reinstated promptly. Additionally, mental health support should not be neglected as it plays a vital role in helping women and children cope with the traumatic experiences they have endured during war times. By taking assertive action now, we can alleviate the suffering of those affected and work towards a healthier future for all.
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Lots of studies in adults and children, mainly done in HICs, are advocating antibiotics only (conservative) management of acute non-perforated appendicitis. In LMICs, with poor access to healthcare, most patients present with perforation. Is there a role of conservative management of acute non-perforated appendicitis in children in LMICs?
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The role of conservative management of acute non perforated appendicitis in children is fairly well established (Jumah S, Wester T. Non-operative management of acute appendicitis in children. Pediatr Surg Int. 2022 Nov 28;39(1):11. doi: 10.1007/s00383-022-05284-y. PMID: 36441297
Armstrong J, Merritt N, Jones S, Scott L, Bütter A. Non-operative management of early, acute appendicitis in children: is it safe and effective? J Pediatr Surg. 2014 May;49(5):782-5. doi: 10.1016/j.jpedsurg.2014.02.071. Epub 2014 Feb 22. PMID: 24851770).
With special reference to the same in the setting of LMIC, the COVID pandemic has brought an increased thrust of its use (Hannan MJ, Parveen MK, Hoque MM, Chowdhury TK, Hasan MS, Nandy A. Management of Acute Appendicitis in Children During COVID-19 and Perspectives of Pediatric Surgeons From South Asia: Survey Study. JMIR Perioper Med. 2021 Dec 21;4(2):e26613.). The evidence for its successful implementation is worth the effort with appropriate inclusion / choice of cases.
Unpublished data from our centre supports the use of non operative management in children with early presentation (onset of pain within 2-3 days), absence of significant collection, fecolith on imaging and successful resolution of symptoms by 24 hours of antibiotics.
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According to the following points, describe your opinion:
  1. Economic Impact: Productivity
  2. Social Impact: Healthcare
  3. Ethical and Moral Considerations
  4. Legal and Governance Issues: Regulation
  5. Technological Advancements: Innovation
  6. Cybersecurity
  7. Environmental Impact: Sustainability
  8. Cultural and Creative Fields
  9. Global Dynamics: Geopolitics
  10. Digital Divide
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Despite the importance of artificial intelligence, especially in the field of the health sector and other magazines, the negatives outweigh the positives, especially in terms of ethics and the labor sector, as there are many fields in the labor sector that will disappear, leading to the spread of unemployment, and this affects the economic, social and political structure in the country. the society.
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Telemedicine in Disaster Response: Explore how telemedicine can be leveraged in disaster situations, such as natural disasters or pandemics, to provide remote medical assistance and triage.
Patient Experience and Satisfaction: Research factors affecting patient satisfaction and engagement in telemedicine, including usability, accessibility, and trust in virtual healthcare.
Telemedicine for Rural Healthcare Access (SDG 3):Investigate how telemedicine can address healthcare disparities in rural and underserved areas, contributing to SDG 3 (Good Health and Well-being).
Telemedicine for Health Equity (SDG 10): Study how telemedicine can reduce health disparities and promote equitable access to healthcare, in line with SDG 10 (Reduced Inequality).
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Thank you dear sir, This helped a lot
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Since Titmus and Esping-Andersen, we have always categorized three types of welfare regimes among developed countries. Could we expand this to Asian, Afrian and Latin-america countries? Would such continents have any kind of welfare?
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Share of informal workers is an indicator of "not enough" for defining a separate welfare state model. As, for example, the share of unemployed, the share of high-tech employees, etc.
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Hi.
I was wondering if is there a full list of AI systems in healthcare, I am looking at the names of the projects such as MYCIN, MAYO-Clinic AI-assisted System, and CAD system.
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MEDIP is a recent launched apps which is amazing
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So, I'm a student of MS clinical psychology, currently working on my thesis. I wanted to explore the impact of perceived parenting style on the degree of morality among mental healthcare professionals. I was told that the two variables are from two different domains of life, i.e., perceived parenting style is related to home/domestic domain and the scale for morality is related to occupational domain. And that this makes the variables lack connection.
Is that true?
Can I really not assess this relationship? The impact of PPS on the morality of people in this profession?
Please, a quick answer would be highly appreciated.
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This article might help.
Mental health: The invisible effects of neglected tropical diseases
The psychological burden of disability and stigma has been overlooked, to the detriment of those affected and their carers...
The stigma and exclusion experienced by people with neglected tropical diseases such as lymphatic filariasis or leprosy can take an enormous psychological toll that is often overlooked. “If you speak to any clinician, they’ll say this is a massive issue. We see it every time someone walks into our clinic and they’ve lost their job, or their husband, or had stones thrown at them by children,” says psychiatrist Julian Eaton. Efforts to systematically evaluate the mental-health burden and trial interventions are only slowly ramping up. “The research is really underinvested in at the moment,” Eaton says...
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I would like to know if there are any of research associate or PhD opportunities in primary care field currently open in Singapore. How should improve my qualifications to apply them? i am interested in access, healthcare planning, chronic diseases and quality assessments.
Thank you
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Thank you so much. I will look into them. Should I directly apply to them
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Hello everyone. I am currently doing my undergrad in Industrial Engineering, about to start my thesis and have a keen interest in machine learning but finding appropriate datasets have been tough. If anyone would be kind enough to suggest websites to find datasets related to my field, it would help me a lot. I have already tried Kaggle but had hard luck finding anything worth working on.
Thank you.
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It's great that you're interested in applying machine learning to your field of industrial engineering. Finding relevant datasets can be a challenge, but there are several sources you can explore:
1. UCI Machine Learning Repository: The University of California, Irvine maintains a repository with a wide range of datasets that might be relevant to your research.
2. Data.gov: This U.S. government website provides access to a wealth of datasets across various domains, including industry and engineering.
3. Open Data Platforms: Many cities, states, and organizations have open data platforms where they share data related to various industries. You might find datasets related to manufacturing, supply chain, and more.
4. Academic Journals and Conferences: Check academic journals and conference proceedings related to industrial engineering. Sometimes, they publish datasets along with research papers.
5. Professional Organizations: Organizations related to industrial engineering may provide datasets or links to relevant data sources. Consider checking out resources from organizations like IISE (Institute of Industrial and Systems Engineers).
6. Collaborate with Your University: Your university's research department or professors in the industrial engineering department might have access to datasets or can guide you to relevant sources.
7. Custom Data Collection: In some cases, you might need to collect your own data through surveys, sensors, or experiments, especially if your thesis topic is specific.
Moreover, Kaggle is a popular platform for datasets, and Google Dataset Search is a valuable resource.
8. Kaggle: Kaggle is a well-known platform for data science and machine learning. While you mentioned having difficulty finding datasets there, it's still a valuable resource. You can explore Kaggle's "Datasets" section and use filters to search for datasets relevant to industrial engineering. Additionally, Kaggle hosts data science competitions, and the competition datasets can also be used for research or projects.
9. Google Dataset Search:Google Dataset Search is a search engine specifically designed to help you find datasets. You can enter keywords related to your field, such as "industrial engineering," and it will return datasets available on the web. It's a great tool to discover datasets from various sources that you might not find through traditional search engines.
Remember that finding the right dataset can take some time and effort, but the effort you put into data acquisition is a crucial part of successful machine learning projects. It's also a good opportunity to network with professionals in your field who may have valuable insights or data sources. Furthermor, Kaggle and Google Dataset Search platforms, along with the other suggestions, can significantly expand your options for finding the right dataset for your work. Happy researching and Good luck with your thesis!
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Fear and stress give rise to slavery. Absence of tangible reward (financial and psychological), nepotism, low salary, human rights violations, absence of perspectives of professional development, mental and physical stress cause Chronic Fatigue Syndrome (asthenia of exhaustion) and emotional burnout (Freudenberger, 1974). It's characteristic of "human-to human" professions. I face these problems in adult auditorium. Is it possible and how to ensure effectiveness of professional activity, to support a high level of functionality, to protect human health?
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PROFESSORA DEBI TEM RAZÃO, O SONO DEVE SER DIÁRIO E BEM FEITO PARA A HIGIENE DO CÉREBRO, E OS INTERVALOS, AS PAUSAS DO TRABALHO DEVEM SER FEITAS DE HORA EM HORA, OU SEJA, ESPERAR O FIM DE SEMANA PARA SER FELIZ ESTÁ ERRADO, FUGIR DO BURNOUT É UM TRABALHO DE TODOS OS DIAS E HORAS. ESPERAR 30 DIAS DE FÉRIAS AO FINAL DO ANO, PARA SER FELIZ, É SINAL DE QUE O TRABALHADOR PRECISA SE REEDUCAR PARA VIVER
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I want to do research in Healthcare sector ..Suggest suitable titles for topic approval
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Patient-Centric Healthcare 4.0: Exploring Blockchain’s Role in Enhancing Patient Experience
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Dear ResearchGate'rs,
I am looking for a journal which indexed, high response and fast publication in the field of "Facility Management & Management Systems" in Healthcare.
I have three drafts on:
  • Development of a diagnostic tool for Facility Management System in the health sector.
  • Case study of the diagnosis of a Facility Management System in a Colombian hospital.
  • Development of a hospital infrastructure management model based on Facility Management System harmonized with Colombian and international health quality standards.
Kindly, share your experience and recommendations.
Thank you and greetings.
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Sobur Setiaman, I had already taken into account several of the options that you have indicated to me, however, it is difficult for many of these journals to have a scope aligned with our research.
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The Patient-centered healthcare approach involves empowering patients to take an active role in their care and necessitates that healthcare professionals possess strong communication skills and effectively address patient needs. Additionally, the approach prioritize physical comfort and emotional well-being, as well as respect for patient and family preferences, values, cultural traditions, and socioeconomic conditions.What is the role of f patient-centered healthcare approach in developing medical education curriculum?
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Thank you for the question and the answers above! Besides what you have already highlighted, according to our experience as both lecturer and researcher in medical schools, including patient-centeredness if fundamental to train the future healthcare professional's humanistic skills, which include not only situating and empowering the patients, but also situating the healthcare professional itself as la person dealing with another person.
Students report difficulties to face something as basic as learning how to deal with another human being. Moreover if this human being is in pain, scared, dis-eased and you are the one expecting to be helpful. Medical training is focused on data analysis, decision making, a precise knowledge of pathology, etcetera. Which enclose them in the amaze and the demand of their discipline. But nobody teaches them how to BE WITH a person in need/pain/despair/scared. Some of our students face severe mental health problems when facing real patients/people, and report they do not feel enough prepared by the training methodologies, despite all the readings, exercises, simulations, etc.
It seams that students should be exposed to people/patients since the early years of their training, and not only during interships, to really benefit from-and assimilate a patient-centered healthcare approach.
Thank you.
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Dear Researchers and Academicians,
We are pleased to announce the Call for Papers for our upcoming book on "Secure Big-Data Analytics for Emerging Healthcare in 5G and Beyond: Concepts, Paradigms, and Solutions". The book aims to explore how big data analytics (BDA) can be used securely in emerging healthcare settings leveraging advanced technologies such as 5G networks.
The following tracks will be covered:
Chapter 1: Introduction to Secure Big-Data Analytics in Emerging Healthcare
Chapter 2: Big Data Analytics (BDA) in Healthcare: Security Challenges in Healthcare Big-Data Analytics
Chapter 3: Overview of 5G and beyond Networks: Limitations of 4G-LTE
Chapter 4: Privacy-Preserving Techniques for Big-Data Analytics in Healthcare
Chapter 5: Secure Data Sharing and Collaboration in Healthcare Analytics.
Chapter 6: Trust and Governance in Healthcare Analytics with secured BDA and operational Challenges.
Chapter7 : Decentralized BDA Healthcare Infrastructures.
Chapter8 : Integration of B5G with Big Data forHealthcare:
Big Data-Driven Networking.
Chapter9 : DistributedAnalyticsforSecureandScalableHealthcareApplications,
Chapter10 : CaseStudiesandBestPracticesinSecureHealthcareAnalyticsUseCases.
Important Dates:
Abstract submission deadline - September 10th ,2023
Full chapter acceptance notification - Oct 15,2023
Please note that all submitted papers will undergo a rigorous double-blind review process by an international committee consisting of subject matter experts with significant research experience leading towards better research output
Please prepare the file for abstract for inclusion
Prepare a good chapter of 20-25 pages as per the IET author guidelines. Please refer the guidelines at https://www.theiet.org/publishing/publishing-with-iet-books/guides-and-resources/
Best regards,
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Interesting.
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The Plan-Do-Study-Act (PDSA) cycle is a potent tool for continuous improvement to enhance processes and achieve superior outcomes. The effectiveness, simplicity, and adaptability of this approach provide significant benefits to healthcare professionals to incorporate these concepts into their practice. By using the PDSA cycle in patient care, they can identify and address potential risks, improve patient outcomes, and foster a culture of continuous improvement in healthcare settings.
What is your opinion?
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Thank you for an interesting discussion topic!
In my opinion, the PDSA cycle can indeed be used in healthcare, but only in relation to those processes that are built and documented in the form of business processes (in the classical sense)
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