Internet of Things-Based Machine Learning in Healthcare

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 recordsFocuses on the importance of machine learning algorithms and the significance of Internet of Things infrastructure for healthcare systemsShowcases the application of fog computing architecture and edge computing in novel aspects of modern healthcare servicesDiscusses unsupervised genetic algorithm-based automatic heart disease predictionCovers Internet of Things–based hardware mechanisms and machine learning algorithms to predict the stress level of patientsThe 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.