Harnessing the Power of IoT-Enabled Machine Learning in Healthcare Applications

This edited book explores the integration of machine learning (ML) and the Internet of Things (IoT) in healthcare applications, particularly through image processing technologies. It addresses key research areas where IoT and ML can be applied to solve challenges in healthcare, such as disease diagnosis, security, and privacy in healthcare systems. The book also examines innovative solutions for improving accuracy in real-time healthcare problems. Key topics covered include IoT-enabled ML systems for applications like blood glucose monitoring, body temperature regulation, and heart rate tracking. The book delves into the design and implementation of these systems, providing insight into the latest developments in healthcare technology. Also, the book discusses how ML can be used to manage the scarcity of monitoring data, especially in mental health care and lung cancer prognosis. It also covers the classification of diseases using MRI and ultrasound images, offering new algorithms and approaches for better diagnosis and treatment. This book provides a comprehensive guide to the intersection of IoT, ML, and image processing, showcasing their potential to enhance healthcare systems and addressing critical challenges in the field.