The Internet of Medical Things (IoMT) is a system that collects data from patients with the help of different sensory inputs, e.g., an accelerometer, electrocardiography, and electroencephalography. This text presents both theoretical and practical concepts related to the application of machine learning and Internet of Things (IoT) algorithms in analyzing data generated through healthcare systems.

Illustrates the latest technologies in the healthcare domain and the Internet of Things infrastructure for storing smart electronic health records
Focuses on the importance of machine learning algorithms and the significance of Internet of Things infrastructure for healthcare systems
Showcases the application of fog computing architecture and edge computing in novel aspects of modern healthcare services
Discusses unsupervised genetic algorithm-based automatic heart disease prediction
Covers Internet of Things–based hardware mechanisms and machine learning algorithms to predict the stress level of patients

The text is primarily written for graduate students and academic researchers in the fields of computer science and engineering, biomedical engineering, electrical engineering, and information technology.

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Yes, you can access Internet of Things-Based Machine Learning in Healthcare by Prasenjit Dey,Sudip Kumar Adhikari,Sourav De,Indrajit Kar in PDF and/or ePUB format, as well as other popular books in Computer Science & Computer Science General. We have over one million books available in our catalogue for you to explore.

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Year

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eBook ISBN

Topic

Subtopic

Computer Science General

Index

Computer Science

Cover
Half-Title
Title
Copyright
Dedication
Contents
Preface
Editors
Contributors
Chapter 1 Applications of Internet of Things and Machine Learning Technologies in Healthcare
Chapter 2 Automated Detection of Patients Developing Anorexia Nervosa and Bulimia Nervosa Using XGBoost Algorithm
Chapter 3 Breast Cancer Prediction Using a Machine Learning Approach
Chapter 4 A Survey on the Development of Deep Learning–Based Techniques in the Diagnosis of Parkinson’s Disease
Chapter 5 A Deep Learning-Based Approach for Detecting Diabetic Retinopathy in Retina Images
Chapter 6 Optimization of CNN for Content-Based Image Retrieval in Healthcare
Chapter 7 Paddy Leaf Diseases Detection Using Otsu and Yen Thresholding with Deep Convolutional Neural Network
Chapter 8 Applications of IoT-Enabled Systems in Healthcare Industry
Chapter 9 Enhancing Health and Environmental Monitoring: Open-Source IoT-Enabled SCADA System with Node-RED, InfluxDB, Grafana, and Raspberry Pi
Chapter 10 Transfer Learning for Healthcare
Chapter 11 Conclusions
Index

About this book

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