Machine Learning and Internet of Medical Things in Healthcare
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Quantity: Over 20 available
Add to basketProvides an introduction to the Internet of Medical Things through the principles and applications of machine learning Explains the functions and applications of machine learning in various applications such as ultrasound imaging, biomedic.
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Machine Learning and the Internet of Medical Things in Healthcare discusses the applications and challenges of machine learning for healthcare applications. The book provides a platform for presenting machine learning-enabled healthcare techniques and offers a mathematical and conceptual background of the latest technology. It describes machine learning techniques along with the emerging platform of the Internet of Medical Things used by practitioners and researchers worldwide.
The book includes deep feed forward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology. It also presents the concepts of the Internet of Things, the set of technologies that develops traditional devices into smart devices. Finally, the book offers research perspectives, covering the convergence of machine learning and IoT. It also presents the application of these technologies in the development of healthcare frameworks.
Dr. Krishna Kant Singh, currently the esteemed Director of Delhi Technical Campus in Greater Noida, India, is a highly experienced educator and researcher in the field of engineering and technology. He is a B.Tech and M.Tech degree, a Postgraduate Diploma in Machine Learning and Artificial Intelligence from IIIT Bangalore, a Master of Science in Machine Learning and Artificial Intelligence from Liverpool John Moores University, United Kingdom, and a Ph.D. from IIT Roorkee. Dr. Singh has made significant contributions to the academic and research community. With over 19 years of teaching experience, he has played a vital role in educating and mentoring future professionals. Dr. Singh also serves as an Associate Editor at IEEE Access, an Editorial Board Member at Applied Computing and Geosciences (Elsevier), and a Guest Editor for Complex and Intelligent Systems. His extensive publication record includes over 132 research papers. His areas of interest include Machine Learning, Deep Learning, computer vision and so on.
Prof. Akansha Singh, Professor at the School of Computer Science and Engineering, Bennett University, Greater Noida, boasts a comprehensive academic background with a B.Tech, M.Tech, and Ph.D. in Computer Science. Her doctoral studies, conducted at the prestigious IIT Roorkee, were focused on the cutting-edge fields of image processing and machine learning. A prolific author and scholar, Dr. Singh has contributed over 100 research papers and penned more than 25 books. Her editorial expertise is recognized by leading publishers such as Elsevier, Taylor and Francis, and Wiley, where she has edited books on a variety of emerging topics.Dr. Singh serves as the Associate Editor in IEEE Access, Discover Applied Science, PLOS One and guest editor in several journals. Her research interests are diverse and influential, spanning image processing, remote sensing, the Internet of Things (IoT), Blockchain and machine learning. Prof. Singh’s work in these areas not only advances the field of computer science but also significantly contributes to the broader scientific and technological community.
Dr. Ahmed A. Elngar is an Associate Professor and Head of the Computer Science Department at the Faculty of Computers and Artificial Intelligence, Beni-Suef University, Egypt. He also serves as an Associate Professor at the American University in the Emirates and as an Adjunct Professor at Woxsen University, India. He is the Founder and Head of the Scientific Innovation Research Group (SIRG) and Director of the Technological and Informatics Studies Center (TISC) at Beni-Suef University. Dr. Elngar has authored over 150 scientific papers and more than 35 books in areas such as data mining, intelligent systems, IoT, and smart environments. His research interests include network security, intrusion detection, AI, machine learning, healthcare systems, and cryptology. He is a member of the Egyptian Mathematical Society and the International Rough Set Society and actively contributes as an editor and reviewer for various international journals. Dr. Elngar is a highly collaborative and interdisciplinary researcher.
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