Medical Big Data and Internet of Medical Things: Advances, Challenges and Applications
CRC Press | English | 2019 | ISBN-10: 1138492477 | 356 pages | PDF | 27.10 MB
Medical Big Data and Internet of Medical Things: Advances, Challenges and Applications
CRC Press | English | 2019 | ISBN-10: 1138492477 | 356 pages | PDF | 27.10 MB
Computer Science by Aboul Ella Hassanien (Editor), Nilanjan Dey (Editor), Surekha Borra (Editor)
This book addresses recent advances in mining, learning, and analysis of big volume of medical images. The book presents taxonomies, trends and issues such as veracity in distributive, dynamic, and diverse data collection, data management, data models, hypotheses testing, training, validation, model-building, optimization techniques and governance of medical big data collected from multiple, heterogeneous IoT devises, networks, platforms and systems such as private vs. public cloud. The book includes privacy, trust, and security issues related to medical Big Data and related IoT and presents case studies in healthcare analytics as well
About the Author
Nilanjan Dey is an Assistant Professor in the Department of Information Technology, Techno India College of Technology, Kolkata, W.B., India. He holds an honorary position of Visiting Scientist at Global Biomedical Technologies Inc., CA, USA and Research Scientist of Laboratory of Applied Mathematical Modeling in Human Physiology, Territorial Organization of- Scientific and Engineering Unions, BULGARIA. Associate Researcher of Laboratoire RIADI, University of Manouba, TUNISIA. His research topic is Medical Imaging, Soft computing, Data mining, Machine learning, Rough set, Computer Aided Diagnosis, Atherosclerosis. He has 20 books and 300 international conferences and journal papers.
Surekha Borra is currently a Professor in the Department of ECE, K. S. Institute of Technology, Bangalore, India. She earned her Doctorate in Image Processing from Jawaharlal Nehru Technological University, Hyderabad, India, in 2015. Her research interests are in the areas of Image and Video Analytics, Machine Learning, Biometrics and Remote Sensing. She has published one edited book, several book chapters and research papers to her credit in refereed & indexed journals, and conferences at international and national levels. Her international recognition includes her professional memberships & services in refereed organizations, programme committees, editorial & review boards, wherein she has been a guest editor for 2 journals and reviewer for journals published by IEEE, IET, Elsevier, Taylor & Francis, Springer, IGI-Global etc,. She has received Woman Achiever's Award from The Institution of Engineers (India), for her prominent research and innovative contribution (s)., Woman Educator & Scholar Award for her contributions to teaching and scholarly activities, Young Woman Achiever Award for her contribution in Copyright Protection of Images.
Dr Aboul Ella Hassanein is the Founder and Head of the Egyptian Scientific Research Group (SRGE) and a Professor of Information Technology at the Faculty of Computer and Information, Cairo University. Professor Hassanien is ex-dean of the faculty of computers and information, Beni Suef University. Prof. Hassanien is a collaborative researcher member of the Computational Intelligence Laboratory at the Department of Electrical and Computer Engineering, University of Manitoba. He also holds the Chair of Computer Science and Information Technology at the Egyptian Syndicate of Scientific Professions (ESSP). Dr Hassanien is the founder and head of Africa Scholars Association in Information and Communication Technology. Professor Hassanien has more than 650 scientific research papers published in prestigious international journals and conferences and over 40 books covering such diverse topics as data mining, medical images, Big Data analysis, virtual reality, intelligent systems, social networks and smart environment. His other research areas include computational intelligence, medical image analysis, security, animal identification and multimedia data mining
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