Internet of Things and Machine Learning for Type I and Type II Diabetes: Use cases

Internet of Things and Machine Learning for Type I and Type II Diabetes: Use Cases provides a medium of exchange of expertise and addresses the concerns, needs, and problems associated with Type I and Type II diabetes. Expert contributions come from researchers across biomedical, data mining, and deep learning. This is an essential resource for both the AI and Biomedical research community, crossing various sectors for broad coverage of the concepts, themes, and instrumentalities of this important and evolving area. Coverage includes IoT, AI, Deep Learning, Machine Learning and Big Data Analytics for diabetes and health informatics.

Sujata Dash holds the position of Professor at the Information Technology School of Engineering and Technology, Nagaland University, Dimapur Campus, Nagaland, India, bringing more than three decades of dedicated service in teaching and mentoring students. She has been honoured with the prestigious Titular Fellowship from the Association of Commonwealth Universities, United Kingdom. As a testament to her global contributions, she served as a visiting professor in the Computer Science Department at the University of Manitoba, Canada. With a prolific academic record, she has authored over 200 technical papers published in esteemed international journals, and conference proceedings, and edited book chapters by reputed publishers Serving as a reviewer and Associate Editor for approximately 15 international journals.

Dr. Subhendu Kumar Pani received his Ph.D. from Utkal University, Odisha, India in the year 2013. He is working as a professor at Krupajal Engineering College under BPUT, Odisha, India. He has more than 20 years of teaching and research experience His research interests include Data mining, Big Data Analysis, web data analytics, Fuzzy Decision Making and Computational Intelligence. He is the recipient of 5 researcher awards. In addition to research, he has guided two PhD students and 31 M. Tech students. He has published 150 International Journal papers (100 Scopus index). His professional activities include roles as Book Series Editor (CRC Press, Apple Academic Press, Wiley-Scrivener), Associate Editor, Editorial board member and/or reviewer of various International Journals. He is an Associate with no. of the conference societies. He has more than 250 international publications, 5 authored books, 25 edited and upcoming books; 40 book chapters into his account. He is a fellow in SSARSC and a life member in IE, ISTE, ISCA, and OBA.OMS, SMIACSIT, SMUACEE, CSI.

Bernard Cheung went to Sevenoaks School and studied Medicine at the University of Cambridge. He was Professor of Clinical Pharmacology and Therapeutics at the University of Birmingham before returning to Hong Kong and being appointed the Sun Chieh Yeh Heart Foundation Professor in Cardiovascular Therapeutics. He was a Consultant Physician of Queen Mary Hospital and the Director of the Phase 1 Clinical Trials Units in Queen Mary Hospital and the University of Hong Kong-Shenzhen Hospital. Currently, he is the Biotechnology Director in the Innovation and Technology Commission. He is also the President of the Federation of Medical Societies of Hong Kong and the Editor-in-Chief of Postgraduate Medical Journal. Prof Cheung's main research interest is in cardiovascular diseases and risk factors, including hypertension and the metabolic syndrome.

Gary Tse is a distinguished academic physician-scientist and Professor at the School of Nursing and Health Sciences, Hong Kong Metropolitan University. Appointed to a full professorship in 2019 at Tianjin Medical University's Department of Cardiology, he also holds a joint appointment as Clinical Reader in Public Health Medicine at Kent and Medway Medical School, University of Kent, and serves as Public Health Consultant at the Medical Council's Public Health Directorate. Since 2021, he has been a Visiting Professor at the University of Surrey and Honorary Associate Professor at University College London. An elected member of the European Academy of Sciences and Arts since 2024, Tse has over 200 publications and an H-index of 58. He has secured more than HK$88 million in research funding and supervised 19 doctoral and 13 master students. His research focuses on using big data for cardiovascular risk prediction and developing AI-driven models for chronic diseases.