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...

This book will have a profound impact on the research community by illustrating how machine learning can transform the care of Diabetic Foot Ulcers (DFU). It offers valuable insights into the development and implementation of Decision Support Systems (DSS), which will encourage further research into enhancing machine learning algorithms for DFU prediction, early detection, and personalized treatment strategies. This book aims to bridge the gap between cutting-edge technology and clinical practice, fostering collaboration across disciplines such as computer science, healthcare, and diabetes...