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010 a| 2022057094;

020 a| 9781000891393q| (epub);

020 a| 9781003303374q| (ebook);

020 z| 9781032300788q| (paperback);

020 z| 9781032300764q| (hardback);

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245 00 a| Federated learning for internet of medical thingsh| [electronic resource] :b| concepts, paradigms, and solutions /c| edited by Pronaya Bhattacharya, Ashwin Verma, and Sudeep Tanwar.;

250 a| First edition.;

260 a| Boca Raton ;a| London :b| CRC Press, Taylor & Francis Group,c| 2023.;

300 a| 1 online resource;

504 a| Includes bibliographical references and index.;

506 a| Available only to authorized users.;

520 a| "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. Once IoMT is presented, the shift is 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 presents effective and secured FL schemes, simulations, and practical discussion on use-case scenarios in simple manner. The book tends to create opportunities of healthcare communities to build effective FL solutions around the presented themes, and the divergent ideas that prosper from reading the book. It also intends to present breakthroughs and foster innovation in FL-based research, specifically in IoMT domain. The emphasis is on understanding the contributions of IoMT in healthcare analytics and its aim is to give the insights including evolution, research directions, challenges and the way to empower healthcare services through federated learning. 1. Book is fully focussed on addressing the missing connection between federated learning and healthcare analytics. 2. The book is providing one-stop guide to students, researchers and Industry professionals. 3. Book is oriented towards the material and flow with regard to general introduction, technical aspects and easy to understand right from beginners to advanced healthcare researchers and professionals too. 4. Here, comprehensive elaboration of material is done and published with examples and diagrams followed by easy understandable approaches w.r.t. technical information. The book also intends to cover the issues of 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"--c| Provided by publisher.;

538 a| Mode of access: World Wide Web;

588 a| Description based on print version record and CIP data provided by publisher.;

650 0 a| Medical electronics.=| ^A2836;

650 0 a| Electronic instruments.=| ^A22703;

650 0 a| Ensemble learning (Machine learning)=| ^A1486579;

650 12 a| Internet of Things?| UNAUTHORIZED;

650 22 a| Machine Learning=| ^A1345552;

650 22 a| Medical Informatics Applications=| ^A925690;

650 22 a| Computer Security=| ^A926183;

655 0 a| Electronic books.=| ^A491897;

700 1 a| Bhattacharya, Pronaya.?| UNAUTHORIZED;

700 1 a| Tanwar, Sudeep.?| UNAUTHORIZED;

700 1 a| Verma, Ashwin.?| UNAUTHORIZED;

776 08 i| Print version:t| Federated learning for internet of medical thingsb| First edition.d| Boca Raton ; London : CRC Press, Taylor & Francis Group, 2023z| 9781032300788w| (DLC) 2022057093;

856 40 z| Full text available from Taylor & Francis eBooksu| https://go.openathens.net/redirector/ecu.edu?url=https%3A%2F%2Fwww.taylorfrancis.com%2Fbooks%2F9781003303374;

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Federated learning for internet of medical things concepts, paradigms, and solutions / edited by Pronaya Bhattacharya, Ashwin Verma, and Sudeep Tanwar.

Other author	Bhattacharya, Pronaya.
Other author	Tanwar, Sudeep.
Other author	Verma, Ashwin.
Format	Electronic
Edition	First edition.
Publication Info	Boca Raton ; London : CRC Press, Taylor & Francis Group, 2023.
Description	1 online resource
Supplemental Content	Full text available from Taylor & Francis eBooks
Subjects	Medical electronics. Electronic instruments. Ensemble learning (Machine learning) Internet of Things Machine Learning Medical Informatics Applications Computer Security

Abstract	"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. Once IoMT is presented, the shift is 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 presents effective and secured FL schemes, simulations, and practical discussion on use-case scenarios in simple manner. The book tends to create opportunities of healthcare communities to build effective FL solutions around the presented themes, and the divergent ideas that prosper from reading the book. It also intends to present breakthroughs and foster innovation in FL-based research, specifically in IoMT domain. The emphasis is on understanding the contributions of IoMT in healthcare analytics and its aim is to give the insights including evolution, research directions, challenges and the way to empower healthcare services through federated learning. 1. Book is fully focussed on addressing the missing connection between federated learning and healthcare analytics. 2. The book is providing one-stop guide to students, researchers and Industry professionals. 3. Book is oriented towards the material and flow with regard to general introduction, technical aspects and easy to understand right from beginners to advanced healthcare researchers and professionals too. 4. Here, comprehensive elaboration of material is done and published with examples and diagrams followed by easy understandable approaches w.r.t. technical information. The book also intends to cover the issues of 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"-- Provided by publisher.
Bibliography note	Includes bibliographical references and index.
Access restriction	Available only to authorized users.
Technical details	Mode of access: World Wide Web
Source of description	Description based on print version record and CIP data provided by publisher.
Issued in other form	Print version: Federated learning for internet of medical things First edition. Boca Raton ; London : CRC Press, Taylor & Francis Group, 2023 9781032300788
Genre/form	Electronic books.
LCCN	2022057094
ISBN	9781000891393 (epub)
ISBN	9781003303374 (ebook)
ISBN	(paperback)
ISBN	(hardback)

Federated learning for internet of medical things concepts, paradigms, and solutions / edited by Pronaya Bhattacharya, Ashwin Verma, and Sudeep Tanwar.

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