Mritunjay Rai, PhD – Assistant Professor, Department of Electrical and Electronics Engineering, Shri Ramswaroop Memorial University, Barabanki, U.P., India
Ravindra Kumar Yadav, PhD – Professor and Head, Department of Electronics and Communication Engineering, Raj Kumar Goel Institute of Technology (RKGIT), Ghaziabad U.P., India
Neha Goel, PhD – Associate Professor, Department of Electronics and Communication Engineering, Raj Kumar Goel Institute of Technology (RKGIT), Ghaziabad U.P., India
Mahesh Kumar H. Kolekar, PhD – Associate Professor, Department of Electrical Engineering, Indian Institute of Technology Patna, Bihar, India

Series: Medical Procedures, Testing and Technology; Computer Science, Technology and Applications
BISAC: COM095000; COM094000; MED018000
DOI: https://doi.org/10.52305/MBEF3026

Book Reviews
“This book offers a timely and comprehensive examination of the convergence between IoT and machine learning in healthcare. It brings together forward-thinking research that not only outlines current developments but also anticipates the future direction of intelligent health systems. A must-read for researchers, students, and policy-makers in health tech.” — Dr. Tanmoy Maity, Professor, IIT (ISM), Dhanbad, Jharkhand, India

“Harnessing the Power of IoT-Enabled Machine Learning in Healthcare Applications captures the essence of digital health transformation. It skillfully balances academic depth with real-world relevance, making it an essential resource for engineers, clinicians, and healthcare innovators navigating the evolving tech landscape.” — Dr. Chandan Kumar, Application Engineers-electronics, Arup India Pvt. Limited, Gurugram

“As a healthcare professional, I found this book profoundly insightful. It translates complex technical advancements into tangible solutions that can improve patient care, diagnostics, and health outcomes. This volume bridges the gap between technology and clinical practice in a meaningful way.”— Dr. Mohd. Danish Nadeem, Post-doc Fellow, IISc. Banglore

Description
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.

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