1st Edition

Federated Learning for Internet of Medical Things Concepts, Paradigms, and Solutions

Edited By Pronaya Bhattacharya, Ashwin Verma, Sudeep Tanwar Copyright 2023
    306 Pages 104 Color & 25 B/W Illustrations
    by CRC Press

    306 Pages 104 Color & 25 B/W Illustrations
    by CRC Press

    This book intends to present emerging Federated Learning (FL)-based architectures, frameworks, and models in Internet of Medical Things (IoMT) applications. It intends to build on the basics of the healthcare industry, the current data sharing requirements, and security and privacy issues in medical data sharing. Once IoMT is presented, the book shifts towards the proposal of privacy-preservation in IoMT, and explains how FL presents a viable solution to these challenges. The claims are supported through lucid illustrations, tables, and examples that present effective and secured FL schemes, simulations, and practical discussion on use-case scenarios in a simple manner. The book intends to create opportunities for healthcare communities to build effective FL solutions around the presented themes, and to support work in related areas that will benefit from reading the book. It also intends to present breakthroughs and foster innovation in FL-based research, specifically in the IoMT domain. The emphasis of this book is on understanding the contributions of IoMT to healthcare analytics, and its aim is to provide insights including evolution, research directions, challenges, and the way to empower healthcare services through federated learning.

    The book also intends to cover the ethical and social issues around the recent advancements in the field of decentralized Artificial Intelligence. The book is mainly intended for undergraduates, post-graduates, researchers, and healthcare professionals who wish to learn FL-based solutions right from scratch, and build practical FL solutions in different IoMT verticals.


    About the Editors

    List of Contributors

    1. Potentials of Internet of Medical Things: Fundamentals and Challenges

    Tanisha Mishra, Shikha Singh, Bramah Hazela,and Garima Srivastava

    2. Artificial Intelligence Applications for IoMT

    Vivek Kumar Prasad, Jainil Solanki, Pronaya Bhattacharya, Ashwin Verma, and Madhuri Bhavsar

    3. Privacy and Security in Internet of Medical Things

    Karthik Ajay, Abhishek S. Mattam, Bivin Joseph, Sohan R., and Ramani Selvanambi

    4. IoMT Implementation: Technological Overview for Healthcare Systems

    Neha Sharma, Sadhana Tiwari, Md Ilyas, Rajeev Raghuvanshi, and Ashwin Verma

    5. A New Method of 5G-Based Mobile Computing for IoMT Applications

    Javaid A. Sheikh, Sakeena Akhtar, and Rehana Amin

    6. Trusted Federated Learning Solutions for Internet of Medical Things

    Sagar Lakhanotra, Jaimik Chauhan, Vivek Kumar Prasad, and Pronaya Bhattacharya

    7. Early Prediction of Prevalent Diseases Using IoMT

    Jigna Patel, Jitali Patel, Rupal Kapdi, and Shital Patel

    8. Trusted Federated Learning for Internet of Medical Things: Solutions and Challenges

    Sajid Nazir, Yan Zhang, and Hua Tianfield

    9. Security and Privacy Solutions for Healthcare Informatics

    Pranshav Gajjar, Shivani Desai, Akash Vegada, Pooja Shah, and Tarjni Vyas

    10. IoT-Based Life-Saving Devices Equipped with Ambu Bags for SARS-CoV-2 Patients

    Ankit Jain and Anita Shukla

    11. Security and Privacy in Federated Learning–Based Internet of Medical Things

    Swathi J., G.R. Karpagam, and Raghvendra Singh

    12. Use-Cases and Scenarios for Federated Learning Adoption in IoMT

    Jonathan Atrey and Ramani Selvanambi

    13. Blockchain for Internet of Medical Things

    Pranalini Joshi and Prasad Gokhale



    Pronaya Bhattacharya, Ashwin Verma, Sudeep Tanwar