Convergence of Internet of Medical Things (IoMT) and Generative AI

Convergence of Internet of Medical Things (IoMT) and Generative AI

Pages: 300
DOI: 10.4018/979-8-3693-6180-1
ISBN13: 9798369361801|ISBN13 Softcover: 9798369361849|EISBN13: 9798369361818
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Description & Coverage
Description:

In recent years, the convergence of the Internet of Medical Things (IoMT) and Generative Artificial Intelligence (AI) has revolutionized healthcare delivery, offering unprecedented opportunities to enhance patient care, improve clinical outcomes, and optimize healthcare systems globally. IoMT based smart healthcare system is a collection of several smart medical equipment including wearable devices and apps connected within the network to provide health information. IoMT refers to interconnected medical devices, wearables, sensors, and healthcare systems that collect, transmit, and analyze health data, while Generative AI encompasses advanced computational techniques capable of generating novel insights, predictions, and solutions. The AI-driven IoMT healthcare system is a combination of IoT (used for periodic control) and AI (used for data analysis).

Generative AI has the potential to revolutionize global health across multiple areas, such as medical data synthesis, image enhancement, disease prediction and diagnosis, drug discovery, medical documentation, and personalized healthcare. It offers opportunities to overcome data scarcity and privacy concerns through synthetic data generation and supports accurate disease interpretation and diagnosis through image quality enhancement. Generative AI models also enable disease likelihood prediction, early condition detection, precise diagnoses, and personalized treatment plans for improved patient care. However, as IoMT and Generative AI continue to proliferate across healthcare ecosystems, it is imperative to critically examine their impact on global health, considering diverse socio-economic contexts, cultural sensitivities, and ethical implications. This book seeks to explore the multifaceted dimensions of IoMT and Generative AI in the context of global health, and introduce emerging applications, integration challenges, regulatory considerations, and future directions for innovation and collaboration.

The book presents a fully understanding on recent advancements in Internet of Medical Things (IoMT) and Generative AI, with a focus on state-of-the-art approaches, methodologies, and systems for the design, development, deployment, and innovative use of those technologies, and it provides insight for how to develop IoMT and generative AI technologies to meet smart business and society development demands, especially in the healthcare field.

IoMT and Generative AI technologies need to be justified in our days and promoted through a multi-focus approach. The scholar value of this proposed book in anchored in the following key pillars: 1. The focus of the research is on IoMT and Generative AI aimed at revealing best practices in state-of-the-art approaches, methodologies, and systems for the design, development, deployment, and innovative use of those technologies and applications to global health in developed and emerging economies. 2. It provides to Recent Advancements in IoMT and Generative AI students and academics as well to other target market an EXCELLENT match of THEORY and PRACTICE. 3. It gives an excellent opportunity for discussing some of the TOP/HOT topics in IoMT and Generative AI and providing fresh ideas on how real world challenges set new frontiers for the design, development, deployment, and innovative use of those technologies and applications.

The proposed book has a clear editing strategy:

To be the REFERENCE edition for all those interested in IoMT and Generative AI technologies focused on state-of-the-art approaches, methodologies, and systems for the design, development, deployment, and innovative use of those technologies in the current and post- pandemic future. [with main emphasis to be paid on practical aspects]. To be the REFERENCE edition for all those (academics and practitioners) interested in the experiences of IoMT and Generative AI technologies for current and future environments. The proposed book aims to be the leading source of information for all those interested in IoMT and Generative AI’ development situation, innovative patterns, systems and solutions, technology policies and strategies as well as their roles in improving global health since it promotes scientific discussion on technologies and solutions of IoMT and Generative AI for global health in developed and emerging economies, as well as to cover the emerging research topics which are going to define the future of IoMT and Generative AI development.

Potential benefits for readers:

1. State of the art contents 2. Excellent showcases on how technologies and solutions can work in practice 3. Unique presentation of increasingly important regions (like Asia-Pacific, South America, Arab World, Africa) through technology development lenses 4. Complimentary views and number of case studies  The development of this reference book is targeting to huge audiences aiming to communicate knowledge on a timely topic. The contribution to the literature of IoMT and Generative AI technologies to advance global health in emerging economies will be significant: Current publications do not focus jointly in the three areas.

Coverage:
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Editor/Author Biographies
Dr. V.Vinoth Kumar, B.Tech, M.Tech., Ph.D, MISTE, is a professor at the Department of Computer Science and Engineering, Jain University. Research Areas: Wireless networks, Artificial Intelligence, Internet of Things (IoT), Big data, Computational technologies.
Polinpapilinho F. Katina is Assistant Professor (Tenure track) in the Department of Informatics and Engineering Systems at the University of South Carolina Upstate (Spartanburg, South Carolina, USA). His areas of research/teaching interests include, among others, Complex System Governance, Critical Infrastructure Systems, Decision Making and Analysis (under uncertainty), Emerging Technologies, Energy Systems (Smart Grids), Engineering Management, Infranomics, Manufacturing Systems, System-of-Systems, Systems Engineering, Systems pathology, and Systems Thinking.
Jingyuan Zhao obtained her PhD in Management Science and Engineering from University of Science and Technology of China (accredited by AACSB and EQUIS). Dr. Zhao's research expertise includes management of technology innovation, technology strategy, behavior and information technology, regional innovation systems and global innovation networks, high-tech industries, multinational governance, and science and technology policy. She has teaching experience of 15 years at the graduate and undergraduate level. Research portfolio includes more than fifty peer-reviewed articles in highly regarded journals, authored books, multiple book chapters, and conference presentations. Dr. Zhao also has extensive industry experience and provides consulting services to major corporations such as China Mobile. She serves as editor-in-chief of International Journal of e-Collaboration(IJeC). Currently she is a professor at University of Toronto.
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