Elias HossainNorth South University · Department of Electrical Engineering and Computer Science
Elias Hossain
Currrently working on AI/ML techniques applied in healthcare
About
19
Publications
37,675
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
99
Citations
Citations since 2017
Introduction
My background education and research exposure during my research career have honed my skill sets to approach a problem from various perspectives. I have excellent interpersonal skills and capable of researching to resolve problems. I have a good understanding of quantitative and qualitative research methods and have good skills in designing software systems. I have a solid knowledge of machine learning, natural language processing, and deep learning.
Publications
Publications (19)
Background: Natural Language Processing (NLP) is widely used to extract clinical insights from Electronic Health Records (EHRs). However, the lack of annotated data, automated tools, and other challenges hinder the full utilisation of NLP for EHRs. Various Machine Learning (ML), Deep Learning (DL) and NLP techniques are studied and compared to unde...
Background:
Natural Language Processing (NLP) is widely used to extract clinical insights from Electronic Health Records (EHRs). However, the lack of annotated data, automated tools, and other challenges hinder the full utilisation of NLP for EHRs. Various Machine Learning (ML), Deep Learning (DL) and NLP techniques are studied and compared to und...
Abstract—The Covid 19 beta coronavirus, commonly known
as the severe acute respiratory syndrome coronavirus 2 (SARS�CoV-2), is currently one of the most significant RNA-type
viruses in human health. However, more such epidemics occurred
beforehand because they were not limited. Much research has
recently been carried out on classifying the disease....
In this modern era, travelling has become an inevitable activity for medium-high income people and students to
energise their mental strength. As a result, they tried to have a
budget tour, such as finding a cheap place to stay or purchasing
a cheap ticket. Although, numerous systems have been developed
to target travel, yet, innumerable gaps exist...
This study is divided into risk factor analysis (RFA) and proposed system architecture (PSA). The light gradient boosting machine (LightGBM) algorithm in the RFA will work with the PSA to predict the risk factors. The results, efficacy, and performance will be validated via a ROC-AUC curve. Therefore, a system usability scale (SUS) procedure will b...
COVID-19, caused by SARS-CoV-2, has been declared as a global pandemic by WHO. Early diagnosis of COVID-19 patients may reduce the impact of coronavirus using modern computational methods like deep learning. Various deep learning models based on CT and chest X-ray images are studied and compared in this study as an alternative solution to reverse t...
Due to the difficulties of brain tumor segmentation, this paper proposes a strategy for extracting brain tumors from three-dimensional Magnetic Resonance Image (MRI) and Computed Tomography (CT) scans utilizing 3D U-Net Design and ResNet50, taken after by conventional classification strategies. In this inquire, the ResNet50 picked up accuracy with...
Depression is a crippling affliction and affects millions of individuals around the world. In general, the physicians screen patients for mental health disorders on a regular basis and treat patients in collaboration with psychologists and other mental health experts, which results in lower costs and improved patient outcomes. However, this strateg...
Background: The rise of COVID-19 has caused immeasurable loss to public health globally. The world has faced a severe shortage of the gold standard testing kit known as reverse transcription-polymerase chain reaction (RT-PCR). The accuracy of RT-PCR is not 100%, and it takes a few hours to deliver the test results. An additional testing solution to...
Diabetes Mellitus is one of the most severe diseases, and many studies have been conducted to anticipate diabetes. This research aimed to develop an intelligent mobile application based on machine learning to determine the diabetic, pre-diabetic, or non-diabetic without the assistance of any physician or medical tests. This study's methodology was...
Verifying Bangla Fake news is challenging, especially if there are many updates from various sources such as social media or online news portals. This study aims to identify the Bangla fake news article; therefore, our Corpus is trained with 57,000 Bangla news items related to trustworthiness and counterfeit. In this study, 95% and 94% accuracy wer...
Domestic violence (DV) is not new. Yet, researchers and human rights experts are reporting an alarming rise in DV against women since countries began locking down areas to stop the virus from spreading. They are now calling for a way to assist victims without risking infection of the virus. This paper proposes a mobile application that addresses DV...
This paper proposes a mobile application named “Sightless Helper”, for assisting blind or visually impaired people. The application uses footstep counting and GPS for indoor and outdoor navigation. It can detect objects and unsafe areas to ensure safe navigation. The system consists of voice recognition, touchpad, button and shaking sensor for easy...
This paper reflects on the implementation of IoT enabled Farming, especially for the people needed a smart way of agriculture. This research focuses on real-time observation with efficient use of cheapest security system. The features of this research including i) Sensor data monitoring using soil moisture sensor which is responsible for measuring...
This paper reflects on the issue of assisting maternity in Bangladesh. We developed a compact solution that can help people as well as educate people on maternity issues-particularly in Bangladesh. The goal of this paper is to assess the applicability and usability for spreading the importance of maternity awareness as well as assisting pregnant wo...
This paper reflects on the indemnity of women in our society. The proposed model ensures the embodiment of a mobile application. The algorithm, we developed for this model focuses the safety issues which is applicable to both inside as well as outside of the house for the women in Bangladesh. The solution of this problems can be done through some i...
Kidnapping and harassment is not only a global
issue but also a historic issue in Bangladesh. In between the years
of 2010 and 2018, the total number of kidnapping events were
found, 6708 (Avg. 745.33 events per year) in Bangladesh. The
government is trying to capture and punish the kidnappers. But
there are a few ways by which the victim can also...
Questions
Questions (9)
Hi there,
I'm currently having trouble exporting a PyTorch model, specifically the AlignTTS model from coqui-ai, to the ONNX format using the onnx.export() function with opset_version=12. The error message I'm getting states that the aten::unflatten operator is not supported for this opset version.
I was wondering if anyone has any suggestions for a workaround or alternative solution to this issue. I've also posted this issue on PyTorch's official GitHub page (https://github.com/pytorch/pytorch/issues/100826).
Thank you in advance for any assistance you can provide.
I will be more than happy to have your suggestions, I am trying to understand the current challenges in clinical NLP, the articles I found do not mention the main challenges, I found some general challenges like de-identification, abbreviation etc.
Hello!
I have a sample health dataset that contains clinical notes and descriptions. I have applied for Name Entity Recognition (NER) over the dataset but do not feel the need for any information such as age, gender or address. I would like to apply the de-identification technique on top of the patient's clinical data. Would you please share with me some resources where I can get information on the implementation of de-identification using Python?
Thank you
Hello!
I'm writing a systematic review article on Natural Language Processing (NLP) and planning to submit the paper to a Q1 journal. Would you please recommend a list of free Q1 journals from where I will receive a fast decision?
I want to customize the ResNet50 pre-trained deep learning model but the problem is I don't understand the aspect I should look at carefully. Simply put, if I want to add extra layers or any parameters, how can these be done?
Is there anyone who can help me share the experience or steps needed to create a model that mimics or customized the ResNet50 model?
It is a long-cherished dream to publish my research paper to the scientific reports-nature as a researcher. I know this is not a good question, but I want to know in detail. My concern is that review articles are indexed in well-cited journals as far as I know because a review article is a combination of many of the state-of-the-art technique's insights. Although I have some research papers in the well-cited Q-1 journal and at the moment, I am thinking of submitting an article to the scientific reports-nature. It would be nice for me if you could give some detailed information about what kind of work is accepted in the computer science domain in nature scientific reports journal and whether the review article can be submitted.
I want to apply some new approaches in the case of sleep apnea. It would be good to get a little suggestion, what kind of technique of ML or DL would be suitable for this disease?
