Internet of Things and Machine Learning for Type I and Type II Diabetes (Paperback)
Language: English
Published by Elsevier - Health Sciences Division, Philadelphia, 2024
- Softcover
- New

Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
AbeBooks seller since October 12, 2005
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Paperback. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Seller Inventory # 9780323956864
- Title
- Internet of Things and Machine Learning for Type I and Type II Diabetes (Paperback)
- Author
- Sujata Dash
- Publisher
- Elsevier - Health Sciences Division, Philadelphia
- Publication year
- 2024
- Condition
- new
- Binding
- Paperback
- Language
- English
- ISBN 10
- 0323956866
- ISBN 13
- 9780323956864
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.
- Integrates many Machine learning techniques in biomedical domain to detect various types of diabetes to utilizing large volumes of available diabetes-related data for extracting knowledge
- It integrates data mining and IoT techniques to monitor diabetes patients using their medical records (HER) and administrative data
- Includes clinical applications to highlight contemporary use of these machine learning algorithms and artificial intelligence-driven models beyond research settings
"Synopsis" may belong to another edition of this title.
About the Author
Subhendu Kumar Pani received his PhD from Utkal University, Odisha, India, in 2013. He currently serves as Principal of Krupajal Engineering College, Bhubaneswar, India, and has over 17 years of teaching and research experience. A prolific author, he serves as Series Editor for CRC Press’ Advances in Computational Collective Intelligence, Apple Academic Press’ AAP Advances in Artificial Intelligence & Robotics, and Wiley-Scrivener’s Intelligent Data Analytics for Terror Threat Prediction, and is actively involved as an associate editor, editorial board member, and reviewer for several international journals. He also contributes to national and international conference communities. His research interests include data mining, big data analytics, web data analytics, fuzzy decision-making, and computational intelligence. He is a Fellow of SSARS (Canada) and a Life Member of several professional bodies, including IE, ISTE, ISCA, OBA, OMS, SMIACSIT, SMUACEE, and CSI. He has received multiple research awards in recognition of his contributions.
Willy Susilo received his Ph.D. degree in Computer Science from the University of Wollongong, Australia. He is a Distinguished Professor the Head of the School of Computing and Information Technology and the director of the Institute of Cybersecurity and Cryptology (iC2) at the University of Wollongong. Recently, he was awarded an Australian Laureate Fellowship, which is the most prestigious award in Australia, due to his contribution in cloud computing security. He was previously awarded a prestigious ARC Future Fellow by the Australian Research Council (ARC) and the Researcher of the Year award in 2016 by the University of Wollongong. He is a Fellow of IEEE, Australian Computer Society (ACS), IET and AAAI. His main research interests include cybersecurity, cryptography and information security. His work has been cited more than 25,000 times in Google Scholar. He is the Editor-in-Chief of the Elsevier Computer Standards and Interfaces and the MDPI Information journal. He has served as a program committee member in dozens of international conferences. He is currently serving as an Associate Editor in several international journals, including IEEE Transactions in Dependable and Secure Computing. Previously, he has served in many top-tier journals, such as IEEE Transactions in Information Forensics and Security. He has published more than 500 research papers in the area of cybersecurity and cryptology.
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 medical scientist focusing on personalized care, health informatics and big data analytics. He is a professor in Hong Kong Metropolitan University and holds a joint position as reader at the University of Kent and public health consultant at the Medway Council in local government, UK. He serves as a professor at the Department of Cardiology and principal investigator at the Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, China. He is a visiting professor at the Faculty of Health and Medical Sciences, University of Surrey, and an honorary associate professor at the School of Pharmacy, University College London. He is an author of more than 500 scientific papers and an expert reviewer for >50 international journals in cardiology, cardiac electrophysiology, cardiovascular biology and epidemiology and five grant bodies from New Zealand, Poland, Sweden and the UK.
"About the title" may belong to another edition of this title.
Grand Eagle Retail
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