Vassilios S. Verykios

Hellenic Open University · School of Science and Technology

This study leverages the DCTPep database, a comprehensive repository of cancer therapy peptides, to explore the application of machine learning in accelerating cancer research. We applied Principal Component Analysis (PCA) and K-means clustering to categorize cancer therapy peptides based on their physicochemical properties. Our analysis identified...

In Generative Artificial Intelligence (AI), Large Language Models (LLMs) like GPT-4, Gemini, Claude, and Llama, significantly impact healthcare by aiding in patient care, medical research, and administrative tasks. AI-powered chatbots offer real-time responses and manage chronic diseases, improving patient outcomes and operational efficiency. Howev...

1 Context. Guideline-directed medical therapy of heart failure (HF) primarily targets neurohormonal activation. 2 However, growth hormone (GH) has emerged as a potential treatment for the multiple hormonal deficiency syndrome, 3 which is associated with worse outcomes in HF. 4 Objective. This study evaluates the efficacy and safety of GH therapy in...

Context Guideline-directed medical therapy of heart failure (HF) primarily targets neurohormonal activation. However, growth hormone (GH) has emerged as a potential treatment for the multiple hormonal deficiency syndrome, which is associated with worse outcomes in HF. Objective This study evaluates the efficacy and safety of GH therapy in HF. Dat...

Citation: Sakagianni, A.; Koufopoulou, C.; Koufopoulos, P.; Kalantzi, S.; Theodorakis, N.; Nikolaou, M.; Paxinou, E.; Kalles, D.; Verykios, V.S.; Myrianthefs, P.; et al. Abstract: Background/Objectives: The emergence of antimicrobial resistance (AMR) due to the misuse and overuse of antibiotics has become a critical threat to global public health....

Generative AI, including large language models (LLMs), has transformed the paradigm of data generation and creative content, but this progress raises critical privacy concerns, especially when models are trained on sensitive data. This review provides a comprehensive overview of privacy-preserving techniques aimed at safeguarding data privacy in ge...

Citation: Sakagianni, A.; Koufopoulou, C.; Koufopoulos, P.; Feretzakis, G.; Kalles, D.; Paxinou, E.; Myrianthefs, P.; Verykios, V.S. The Synergy of Machine Learning and Epidemiology in Addressing Carbapenem Resistance: A Comprehensive Review. Antibiotics 2024, 13, 996. https://doi. Abstract: Background/Objectives: Carbapenem resistance poses a sign...

The process of aging leads to a progressive decline in the immune system function, known as immunosenescence, which compromises both innate and adaptive responses. This includes impairments in phagocytosis and decreased production, activation, and function of T-and B-lymphocytes, among other effects. Bacteria exploit immunosenescence by using vario...

Citation: Theodorakis, N.; Feretzakis, G.; Hitas, C.; Kreouzi, M.; Kalantzi, S.; Spyridaki, A.; Boufeas, I.Z.; Sakagianni, A.; Paxinou, E.; Verykios, V.S.; et al. Antibiotic Resistance in the Elderly: Mechanisms, Risk Factors, and Solutions. Microorganisms 2024, 12, 1978. https://doi. Abstract: Antibiotic resistance presents a critical challenge in...

Large Language Models (LLMs) have transformed natural language processing (NLP) by enabling robust text generation and understanding. However, their deployment in sensitive domains like healthcare, finance, and legal services raises critical concerns about privacy and data security. This paper proposes a comprehensive framework for embedding trust...

Introduction: The aim of this study was to evaluate alterations in corneal astigmatism, axial anterior corneal curvature, anterior chamber depth, and central corneal thickness (CCT) two months after the unilateral recession of lateral rectus muscle in children. Methods: This prospective study included 37 children with intermittent exotropia who wou...

This study introduces a hybrid text summarization technique designed to enhance the analysis of qualitative feedback from online educational surveys. The technique was implemented at the Hellenic Open University (HOU) to tackle the challenges of processing large volumes of student feedback. The TextRank and Walktrap algorithms along with GPT-4o min...

Background: The ASCAPE project aims to improve the health-related quality of life of cancer patients using artificial intelligence (AI)-driven solutions. The current study employs a comprehensive dataset to evaluate sleep and urinary incontinence, thus enabling the development of personalized interventions. Methods: This study focuses on prostate c...

Aging is a fundamental biological process characterized by a progressive decline in physiological functions and an increased susceptibility to diseases. Understanding aging at the molecular level is crucial for developing interventions that could delay or reverse its effects. This review explores the integration of machine learning (ML) with multi-...

Introduction This nationwide study aims to analyze mortality trends for all individual causes in Greece from 2001 to 2020, with a specific focus on 2020 - a year influenced by the coronavirus pandemic. As Greece is the fastest-aging country in Europe, the study’s findings can be generalized guiding the re-evaluation of global health policies. Meth...

In this report, we present the collaborative efforts between the Open University (OU) in the UK and Hellenic Open University (HOU) in Greece, aimed at designing a predictive learning analytics dashboard with recommendation services for online and distance students. This initiative seeks to offer students personalized feedback throughout their acade...

In an era increasingly focused on integrating Artificial Intelligence (AI) into healthcare, the utility and user satisfaction of AI applications like ChatGPT have become pivotal research areas. This study, conducted in Greece, engaged 193 doctors from various medical departments who interacted with ChatGPT 4.0 through a custom web application. The...

In the realm of ophthalmic surgeries, silicone oil is often utilized as a tamponade agent for repairing retinal detachments, but it necessitates subsequent removal. This study harnesses the power of machine learning to analyze the macular and optic disc perfusion changes pre and post-silicone oil removal, using Optical Coherence Tomography Angiogra...

This study investigates the forecasting of cardiovascular mortality trends in Greece's elderly population. Utilizing mortality data from 2001 to 2020, we employ two forecasting models: the Autoregressive Integrated Moving Average (ARIMA) and Facebook's Prophet model. Our study evaluates the efficacy of these models in predicting cardiovascular mort...

The intersection of COVID-19 and pulmonary embolism (PE) has posed unprecedented challenges in medical diagnostics. The critical nature of PE and its increased incidence during the pandemic underline the need for improved detection methods. This study evaluates the effectiveness of advanced deep learning techniques in enhancing PE detection in post...

Currently, several techniques based on probabilities and statistics, along with the rapid advancements in computational power, have deepened our understanding of a football match result, giving us the capability to estimate future matches' results based on past performances. The ability to estimate the number of goals scored by each team in a footb...

In this AI-focused era, researchers are delving into AI applications in healthcare, with ChatGPT being a primary focus. This Greek study involved 182 doctors from various regions, utilizing a custom web application connected to ChatGPT 4.0. Doctors from diverse departments and experience levels engaged with ChatGPT, which provided tailored response...

The study explores the application of automated machine learning (AutoML) using the MIMIC-IV-ED database to enhance decision-making in emergency department (ED) triage. We developed a predictive model that utilizes triage data to forecast hospital admissions, aiming to support medical staff by providing an advanced decision-support system. The mode...

SharedIt link: https://rdcu.be/dO7fN Population aging is a global phenomenon driving research focus toward preventing and managing age-related disorders. Functional hypogonadism (FH) has been defined as the combination of low testosterone levels, typically serum total testosterone below 300–350 ng/dL, together with manifestations of hypogonadism, i...

Vocational Education and Training (VET) suffers from an increasing rate of stu-dent dropout in the school sector, while it is largely neglected in the learning ana-lytics (LA) research. At the same time school dropout rates are consistently rising globally and researchers are trying to understand why. Some concentrate on its relation to chronic abs...

Prostate cancer is the second most common cancer among men, with many treatment modalities available for patients, such as radical prostatectomy, external beam radiotherapy, brachytherapy, high-intensity focused ultrasound, cryotherapy, electroporation and other whole-gland or focal ablative novel techniques. Unfortunately, up to 60% of men with pr...

1) Background: Predictive modeling is becoming increasingly relevant in healthcare, aiding in clinical decision making and improving patient outcomes. However, many of the most potent predictive models, such as deep learning algorithms, are inherently opaque, and their decisions are challenging to interpret. This study addresses this challenge by e...

Organizations leverage massive volumes of information and new types of data to generate unprecedented insights and improve their outcomes. Correctly identifying duplicate records that represent the same entity, such as user, customer, patient and so on, a process commonly known as record linkage, can improve service levels, accelerate sales, or ele...

The integration of artificial intelligence (AI) into medical practice has become a critical focus in contemporary medical research. This bibliometric analysis examined the scope of AI utilization across the healthcare spectrum by analyzing a significant body of publications from the Sco-pus and PubMed databases. After removing duplicates and review...

In distance learning educational environments like Moodle, students interact with their tutors, their peers, and the provided educational material through various means. Due to advancements in learning analytics, students' transitions within Moodle generate digital trace data that outline learners' self-directed learning paths and reveal informatio...

Distance Learning has become the “new normal”, especially during the pandemic and due to the technological advances that are incorporated into the teaching procedure. At the same time, the augmented use of the internet has blurred the borders between distance and conventional learning. Students interact mainly through LMSs, leaving their digital tr...

Aim: The aim of this study was to prospectively evaluate the changes in macular and optic disc microvascular structures in patients who underwent silicone oil (SO) removal. Materials and methods: A total of 28 patients scheduled for unilateral SO removal were included in the study. Their fellow eyes served as controls. Optical coherence tomography...

This paper investigates the feasibility and potential benefits of implementing a Collaborative Filtering (CF) Recommender System within a Moodle Learning Environment. With the rapid proliferation of e-learning platforms, the integration of sophisticated recommender systems is becoming increasingly critical to mitigate the challenges associated with...

The AI hype has brought on the spotlight technologies that led some circles to argue that we are unleashing AI as a completely untested technology with possibly dangerous implications for society. Despite the scaremongering, AI applications have improved our lives in many fields. In education its implementation has already been made but with minor...

This paper explores the relationship between students' final exam scores and their participation in distance learning forums and platforms. The study investigates whether active engagement in online forums and educational platforms correlates with improved academic performance. Analyzing data from distance learners in Hellenic Open University, the...

In an epoch characterized by the swift pace of digitalization and urbanization, the essence of community well-being hinges on the efficacy of urban management. As cities burgeon and transform, the need for astute strategies to navigate the complexities of urban life becomes increasingly paramount. This study employs time series analysis to scrutini...

Simple Summary In an age where technology is deeply intertwined with healthcare, this review focuses on the synergistic role of artificial intelligence (AI) and radiomics in the management of urological cancers, particularly bladder, kidney, and prostate cancers. Our comprehensive review explores how AI’s rapid data-processing capabilities, combine...

This review article provides an in-depth analysis of the growing field of AI-assisted programming tasks, specifically focusing on the use of code embeddings and transformers. With the increasing complexity and scale of software development, traditional programming methods are becoming more time-consuming and error-prone. As a result, researchers ha...

The field of Natural Language Processing (NLP) has experienced significant growth in recent years, largely due to advancements in Deep Learning technology and especially Large Language Models. These improvements have allowed for the development of new models and architectures that have been successfully applied in various real-world applications. D...

In an epoch characterized by the swift pace of digitalization and urbanization, the essence of community well-being hinges on the efficacy of urban management. As cities burgeon and transform, the need for astute strategies to navigate the complexities of urban life becomes in-creasingly paramount. This study employs time series analysis to scrutin...

Smart cities, leveraging advanced data analytics, predictive models, and digital twin techniques , offer a transformative model for sustainable urban development. Predictive analytics is critical to proactive planning, enabling cities to adapt to evolving challenges. Concurrently, digital twin techniques provide a virtual replica of the urban envir...

Smart cities, leveraging advanced data analytics, predictive models, and digital twin techniques, offer a transformative model for sustainable urban development. Predictive analytics plays a crucial role in proactive planning, enabling cities to adapt to evolving challenges. Concurrently, digital twin techniques provide a virtual replica of the urb...

In Distance Education (DE) the importance of community is often emphasized, as according to many experts in the field, the strong sense of community among learners improves the quality of teaching and learning. In this study, we use the Social Network Analysis (SNA) approach to detect the communities formed in the collaboration networks created by...

A huge amount of data, in terms of streams, are collected nowadays via a variety of sources, such as sensors, mobile devices, or even raw log files. The unprecedented rate at which these data are generated and collected calls for novel record linkage methods to identify matching records pairs, which refer to the same real-world entity. Towards this...

Learning mostly involves communication and interaction that leads to new information being processed, which eventually turns into knowledge. In the digital era, these actions pass through online technologies. Formal education uses LMSs that support these actions and, at the same time, produce massive amounts of data. In a distance learning model, t...

The Expectation Maximization algorithm is used to infer (a) the parameters of underlying Gaussian distributions of a data set and (b) the probability distributions for each data point that denote its membership to each such distribution. In this paper, we, first, provide the theoretical ground of the algorithm, and then, experimentally evaluate its...

Abstract: It is well known that overcrowding in emergency department (ED) lowers the standard of care and raises the risk of medical errors. An initial predictive supplementary tool of hospital admission at an early stage of a patient's arrival to the emergency department (ED) can provide health care professionals a number of advantages, such as, m...

Artificial Intelligence (AI) has shown the ability to enhance the accuracy and efficiency of physicians. ChatGPT is an AI chatbot that can interact with humans through text, over the internet. It is trained with machine learning algorithms, using large datasets. In this study, we compare the performance of using a ChatGPT API 3.5 Turbo model to a g...

ASCAPE Project is a study aiming to implement the advances of Artificial Intelligence (AI), to support prostate cancer survivors, regarding quality of life issues. The aim of the study is to determine characteristics of patients who accepted to join ASCAPE project. It results that participants of the study mainly originate from higher-educated soci...

In this study a deep learning architecture based on a convolutional neural network has been evaluated for the classification of white light images of colorectal polyps acquired during the process of a colonoscopy, to estimate the accuracy of the optical recognition of histologic types of polyps. Convolutional neural networks (CNNs), a subclass of a...

The COVID-19 infection is still a serious threat to public health and healthcare systems. Numerous practical machine learning applications have been investigated in this context to support clinical decision-making, forecast disease severity and admission to the intensive care unit, as well as to predict the demand for hospital beds, equipment, and...

Innovative impact Distance education has emerged as a solution to the limited access and exclusion faced by different groups of students in education. However, technical challenges for openness and inclusion remain to a large extent, unresolved and without a cure in sight. Learning analytics (LA) has gained broad acceptance as a tool to promote inc...

Since its emergence, the COVID-19 pandemic still poses a major global health threat. In this setting, a number of useful machine learning applications have been explored to assist clinical decision-making, predict the severity of disease and admission to the intensive care unit, and also to estimate future demand for hospital beds, equipment, and s...

The purpose of this study was to test the accuracy of different CNNs, compared to the endoscopist’s accuracy for optical diagnosis and the reference standard of histopathologic examination. We prospectively captured 1000 images of 191 polyps, including sessile serrated lesions (SSL) from 86 patients during full colonoscopy using HD white light endo...

Sessile serrated lesions (SSL) constitute a special group of colorectal polyps in terms of difficult recognition and importance in carcinogenesis. The aim of this study was to evaluate the use of convolutional neural networks (CNNs) in the optical prediction of SSL upon endoscopic and histopathologic images.

Machine learning (ML) algorithms are increasingly applied in medical research and in healthcare, gradually improving clinical practice. Among various applications of these novel methods, their usage in the combat against antimicrobial resistance (AMR) is one of the most crucial areas of interest, as increasing resistance to antibiotics and manageme...

Advances in data collection techniques and data storage devices have enabled the collection and persistent storage of data flowing into different operational systems from various sources. Educational systems is not an exception to this rule, and as such continuously generated streams of data related to the interaction among students. Instructors an...

New challenges in education demand effective solutions. Although Learning Analytics (LA), Educational Data Mining (EDM) and the use of Big Data are often presented as a panacea, there is a lot of ground to be covered in order for the EDM to answer the real questions of educators. An important step toward this goal is to implement holistic solutions...

Given several databases containing person-specific data held by different organizations, Privacy-Preserving Record Linkage (PPRL) aims to identify and link records that correspond to the same entity/individual across different databases based on the matching of personal identifying attributes, such as name and address, without revealing the actual...

Distance Learning has often been side by side with the notion of Openness. The MOOCs' hype was partly due to the wide Accessibility that prestigious universities offered to a wide audience of learners who were following along the technological progress and could afford the cost and time expenses for learning sustainably. However, education should a...

A trajectory is a set of traces left by a moving object. It contains spatio-temporal information about where and when that object was, as well as other semantical relevant information. It is described by a continuation of movement. Data concerning moving objects and their trajectories can be stored in a Trajectory Data Warehouses for organization,...

Nowadays, the world is experiencing an intense and prolonged socio-economic crisis, which has been enhanced by the health crisis due to coronavirus. These crises had also a huge effect on the educational system. The academic world had to adjust rapidly and shift its teaching methods and tools to the demands of remote learning. These new circumstanc...