The Internet of Medical Things (IoMT) paradigm focuses on digitizing medical electronics and instruments in hospital environments, connecting them to cloud-hosted healthcare-related content, data, services, and applications through the Internet communication infrastructure. This book also illustrates how such a technological empowerment makes healthcare devices and equipment intelligently autonomous in their decisions, actions, and reactions. It elucidates the latest trends and transitions in the field of IoMT for medical doctors, surgeons, specialists, caregivers, and patients. It covers algorithms used in machine learning, deep learning, reinforcement learning and ensemble learning, as well as the individual steps involved in AI model development, and explains how to analyse healthcare data effectively. Additionally, generative AI tools -including large, small, vision, and multimodal language models -are useful for envisioning and implementing expert decision science, question/answer (Q/A) systems, and conversational AI chatbots to support medical professionals in their work. This book is a handholding guide for healthcare service providers and consumers, AI engineers, 5G, edge computing and IoT architects.
