Federated Learning for Internet of Medical Things

The book intends to present emerging Federated Learning (FL) based architectures, frameworks, and models in Internet-of-Medical Things (IoMT) applications. It intends to build up onto the basics of healthcare industry, the current data sharing requirements, and security and privacy issues in medical data sharing.

Pronaya Bhattacharya, Ashwin Verma, Sudeep Tanwar

1. Potentials of Internet of Medical Things: Fundamentals and Challenges, 2. Artificial Intelligence Applications for IoMT, 3. Privacy and Security in Internet of Medical Things, 4. IoMT Implementation: Technological Overview for Healthcare Systems, 5. A New Method of 5G-Based Mobile Computing for IoMT Applications, 6. Trusted Federated Learning Solutions for Internet of Medical Things, 7. Early Prediction of Prevalent Diseases Using IoMT, 8. Trusted Federated Learning for Internet of Medical Things: Solutions and Challenges, 9. Security and Privacy Solutions for Healthcare Informatics, 10. IoT-Based Life-Saving Devices Equipped with Ambu Bags for SARS-CoV-2 Patients, 11. Security and Privacy in Federated Learning-Based Internet of Medical Things, 12. Use-Cases and Scenarios for Federated Learning Adoption in IoMT, 13. Blockchain for Internet of Medical Things