Elias Hossain

I am a PhD student in Computer Science at Mississippi State University, United States, specializing in the integration of artificial intelligence within healthcare. My research is particularly focused on employing state-of-the-art AI in robotics to enhance healthcare services. I have authored several publications that have appeared in top-tier computer science journals and conferences, which are recognized in both Q1 and Q2 rankings and are indexed in Scopus and ISI. In addition to my academic pursuits, I have three years of professional experience in the software industry. During this time, I developed web and desktop extensions using C#, Python, and ReactJS. Notably, I worked on developing extensions for Microsoft Office applications, including PowerPoint and Excel, specifically tailored for Windows and Linux distributions. My contributions to healthcare include applying deep learning algorithms to detect diseases such as cancer from extensive biomedical imaging data, such as chest X-rays, MRIs, and CT scans. Furthermore, I have explored the application of Large Language Models (LLMs) for clinical text classification and summarization. I have also leveraged these models to develop an educational chatbot using the Django framework. I am dedicated to advancing the field of AI in healthcare and look forward to contributing further innovations and solutions.

Education

Publication

Journal Articles

• Hossain, E., Rana, R., et al. Natural Language Processing in Electronic Health Records in relation to healthcare decision-making: A systematic review. Computers in Biology and Medicine, vol. 155. [Q1, IF: 7.7]
• Hossain, E., Alshehri, M., Almakdi, S., Halawani, H., Rahman, M. M., Rahman, W., ... & Mia, S. Dm-Health App: Diabetes Diagnosis Using Machine Learning with Smartphone. CMC-COMPUTERS MATERIALS & CONTINUA, 72(1), 1713-1746. [Q1, IF: 3.1]
• Hossain, E., Hossain, M. S., Hossain, M. S., Al Jannat, S., Huda, M., Alsharif, S., ... & Rashed, A. N. Z. Brain Tumor Auto-Segmentation on Multimodal Imaging Modalities Using Deep Neural Network. CMC-COMPUTERS MATERIALS & CONTINUA, 72(3), 4509-4523. [Q1, IF: 3.1]
• Hossain, E., Alazeb, A., Almudawi, N., Almakdi, S., Alshehri, M., Faruque, M. G. G., & Rahman, W. Forecasting Mental Stress Using Machine Learning Algorithms. CMC-COMPUTERS MATERIALS & CONTINUA, 72(3), 4945-4966. [Q1, IF: 3.1]
• Siddiqui, S., Arifeen, M., Hopgood, A., Good, A., Gegov, A., Hossain, E., ... & Masum, S. Deep Learning Models for the Diagnosis and Screening of COVID-19: A Systematic Review. SN computer science, 3(5), 1-22. [Scopus]
• Hossain, M. M., Swarna, R. A., Mostafiz, R., Shaha, P., Pinky, L. Y., Rahman, M. M., ... & Iqbal, M. S. Analysis of the performance of feature optimization techniques for the diagnosis of machine learning-based chronic kidney disease. Machine Learning with Applications, 100330.
• Hossain, M. E., Rahman, M. W., Islam, M. T., & Hossain, M. S. Manifesting a mobile application on safety which ascertains women salus in Bangladesh. International Journal of Electrical and Computer Engineering, 9(5), 4355. [Q3, Scopus]




Book Chapters

• Siddiqui, S., Hossain, E., Asaduzzaman, S. M., Al Jannat, S., Niloy, T. S., Rahman, W., ... & Gegov, A. Analysing and Identifying COVID-19 Risk Factors Using Machine Learning Algorithm with Smart- phone Application. In Inventive Systems and Control (pp. 775-788). Springer, Singapore. [Scopus]
• Siddiqui, S., Hossain, E., Ferdous, R., Arifeen, M., Rahman, W., Masum, S., ... & Gegov, A. A Comparative Study of Deep Learning Models for COVID-19 Diagnosis Based on X-Ray Images. In Smart and Sustainable Technology for Resilient Cities and Communities (pp. 163-174). Springer, Singapore.
• Hossain, E., Kaysar, N., Joy, J. U., Md, A. Z., Rahman, M., & Rahman, W. A Study Towards Bangla Fake News Detection Using Machine Learning and Deep Learning. In Sentimental Analysis and Deep Learning (pp. 79-95). Springer, Singapore.
• Siddiqui, S., Hopgood, A., Good, A., Gegov, A., Hossain, E., Rahman, W., ... & Khan, Z. A Next- Generation Telemedicine and Health Advice System. In Proceedings of Sixth International Congress on Information and Communication Technology (pp. 981-989). Springer, Singapore. [Scopus]
• Hossain, M., Qaiduzzaman, K. M., & Rahman, M. Sightless helper: an interactive mobile application for blind assistance and safe navigation. In International Conference on Cyber Security and Computer Science (pp. 581-592). Springer, Cham. [Scopus]
• Qaiduzzaman, K. M., Khatun, S., Afsa, M., Sobhan, S., Hossain, E., M., Shaharum, S. M., & Rahman, M. A Mutation Triggering Method for Genetic Algorithm to Solve Traveling Salesman Problem. In Embracing Industry 4.0 (pp. 159-170). Springer, Singapore. [Scopus]




Conference Articles

• Hossain, M. E., Najib, A. U., & Islam, M. Z. Combating domestic violence during COVID-19 pandemic in Bangladesh: using a mobile application integrated with an effective solution. In 2020 23rd International Conference on Computer and Information Technology (ICCIT) (pp. 1-6). IEEE.
• Hossain, M. E., Rahman, M., Qaiduzzaman, K. M., Shakir, A. K., & Hassan, M. M. Efficient Anti- Kidnapping and Anti-Harassment (Avoidance-Detection-Notification) Mobile Application for Un- wanted Incidents. In 2019 IEEE Student Conference on Research and Development (SCOReD) (pp. 112-116). IEEE. [Scopus]
• Kulsum, M. U., Najib, A. U., & Hossain, M. E. Design And Development Of MGA System: A Maternity Guidance Light Weight Mobile Application. In 2019 IEEE International Conference on Signal Processing, Information, Communication & Systems (SPICSCON) (pp. 54-58). IEEE. [Scopus]
• Jannat, S.A., Hossain, S., & Hossain, E. ADPT: An Automated Disease Prognosis Tool Towards Classifying Medical Disease Using Hybrid Architecture of Deep Learning Paradigm. In 2022 25th International Conference on Computer and Information Technology (ICCIT), Bangladesh. [Scopus]
• Hossain, E., Rahman, M.E., Siddiqui, S., & Masum, S. Hybrid Machine Learning model for A Next- Generation Ecofriendly Travelling and Guides to Reduce Carbon Emissions. In 2022 25th International Conference on Computer and Information Technology (ICCIT), Bangladesh. [Scopus]

Conferences

The Mississippi Innovation Health Conference was held at the historic Christian Center within Millsaps College in Jackson, United States, on 26 March 2024. This event showcased advancements in health informatics and featured presentations from industry experts. I was invited to present my research on AI in healthcare at this conference.

Talking about AI in Healthcare

Unveiling the Latest in Health Innovation

Navigating the Digital Health and Technology

Spotlight on My Poster Research: MIHC 2024

In Discussion with Dr. David, MSU Professor

Spring 2024 Graduate Research Symposium

Awards

• 4th Industrial Revolution (4IR) Skills Award, In Recognition of Notable Contribution in 4IR Skills, Organized by North South University Career and Placement Center in collaboration with Aspire to Innovate (a2i) and Thriving Skills (2023).
• DIU Research Award, In Recognition of Scholarly Publication in Reputed Indexed Journals for 2019, 2020, and 2021, Organized by Division of Research, Daffodil International University, Bangladesh (2021).
• Finalist, Dr. Pradeep P Thevannoor Innovation Awards (PPTIA), Organized by SCMS School of Engineering and Technology (SSET), Kerala, India (2019).
• Champion, University of Asia Pacific (UAP) Software and Hardware Carnival in the Best Innovative Mobile Application Development category (2018).
• Division Champion, NASA SPACE APPS Challenge on the best use of NASA data resources category, Organized by Bangladesh Association of Software and Information Services (BASIS) (2017).
• National Winner, Pilot Round of SS12 Innovation Challenge and Maker Fair at Independent University Bangladesh, Organized by IEEE Bangladesh  Section, IEEE Bangladesh Section Humanitarian Activity Committee (HAC) along with IEEE Independent University Bangladesh Student Branch (2018).