Machine Learning and the Internet of Medical Things in Healthcare

This book PDF is perfect for those who love Science genre, written by Krishna Kant Singh and published by Academic Press which was released on 14 April 2021 with total hardcover pages 290. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Machine Learning and the Internet of Medical Things in Healthcare books below.

Machine Learning and the Internet of Medical Things in Healthcare
Author : Krishna Kant Singh
File Size : 46,7 Mb
Publisher : Academic Press
Language : English
Release Date : 14 April 2021
ISBN : 9780128232170
Pages : 290 pages
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Machine Learning and the Internet of Medical Things in Healthcare by Krishna Kant Singh Book PDF Summary

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. Provides 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, biomedical signal processing, robotics, and biomechatronics Includes coverage of the evolution of healthcare applications with machine learning, including Clinical Decision Support Systems, artificial intelligence in biomedical engineering, and AI-enabled connected health informatics, supported by real-world case studies

Machine Learning and the Internet of Medical Things in Healthcare

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