Biomedical Applications of AI and IoMT in Smart Healthcare

Artificial Intelligence (AI) to the Internet of Medical Things (IoMT) is not just a slight enhancement of healthcare but a paradigm shift. Biomedical Applications of AI and IoMT in Smart Healthcare is a pioneering investigation of this change, filling the divide between highly complex computational methods and the practical clinical applications. This volume includes the most promising products to transform modern medicine, based on real-time monitoring of patients and mental health, to early detection of diabetes, hepatitis C, and skin cancers. This book, edited by a renowned group of professionals, Prashant Upadhyay, Pradeep Tomar, Fadi Al-Turjman and Satya Prakash Yadav, is an assemblage of research work around the world that explores practical applications as well as analytical frameworks. The topics addressed in chapters are quite broad, such as AI-based virtual tutors to learn medicine, HOG-based eye-tracking interfaces, hybrid deep learning networks to diagnose melanoma, and optimized neural networks to diagnose diseases. The book is not only focused on the level of sophistication in technology but also on the accessibility, equity, and the health impact on the world. This volume provides a valuable and timely guide to the ecosystem of the IoMT whether you are a researcher, biomedical engineer, health professional or student of digital health technologies. It shows how smart systems are turning healthcare into a more predictive, personalized and pervasive one algorithm at a time.

Key Features:

• Varied Disease Coverage- Covers specialized AI/IoMT models of diabetes, cervical cancer, hepatitis C, monkeypox, melanoma, asthma, blood group classification, demonstrating a wide clinical applicability.
• Real-World IoMT Integration – A chapters deal with real-time data analysis, patient monitoring, wearable devices, and edge-based fitness coaching with geospatial technology and small language models.
• State-of-the-art AI and ML Approaches – Shows ensemble, transfer learning (ResNet-50 + SVM), perceptron optimization (Penguin Optimization Algorithm), and HOG-based face landmark detection.
• International & Multidisciplinary Authorship - The works of various universities and research centers in India, Turkey, and others will be involved, which will guarantee a multinational outlook to the topic of smart healthcare innovation.
• Bridging Research and Education - Unique focus on AI-powered medical education, virtual tutors, and simulation technologies, which makes it useful in both an academic and clinical training setting.