Название: Federated Learning for Internet of Medical Things: Concepts, Paradigms, and Solutions
Автор: Pronaya Bhattacharya, Ashwin Verma, Sudeep Tanwar
Издательство: CRC Press
Год: 2023
Страниц: 308
Язык: английский
Формат: pdf (true)
Размер: 13.5 MB
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. Federated Learning (FL) is a newly introduced technology that has piqued the interest of researchers eager to investigate its potential and applicability. Federated Learning simply tries to answer the question: “Can we prepare the model without trying to transfer data to a central location?”. Furthermore, Federated Learning allows for training without the need for data dissemination, which was not previously available with typical Machine Learning (ML) techniques.