Internet of Things-Based Machine Learning in Healthcare: Technology and Applications

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.