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Federated learning and AI for health...

Bhattacharya, Pronaya.

Federated learning and AI for healthcare 5.0

Record Type:	Electronic resources : Monograph/item
Title/Author:	Federated learning and AI for healthcare 5.0 edited by Ahdi Hassan, Vivek Prasad, Pronaya Bhattacharya, Pushan Dutta, Robertas Damasevicius.
other author:	Hassan, Ahdi,
Published:	Hershey, Pennsylvania :IGI Global,2024.
Description:	1 online resource (391 p.)
Subject:	Artificial intelligence.
Online resource:	http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-1082-3
ISBN:	9798369310830$q(ebook)

Federated learning and AI for healthcare 5.0
Federated learning and AI for healthcare 5.0[electronic resource] / edited by Ahdi Hassan, Vivek Prasad, Pronaya Bhattacharya, Pushan Dutta, Robertas Damasevicius. - Hershey, Pennsylvania :IGI Global,2024. - 1 online resource (391 p.)

Includes bibliographical references and index.

Chapter 1. Healthcare 5.0 fundamentals -- Chapter 2. Introduction to cloud computing and healthcare 5.0: transforming the future of healthcare -- Chapter 3. Development of personalized healthcare systems (Healthcare 5.0) and its impact on wellbeing: understanding the concepts -- Chapter 4. Intelligent biosensors for Healthcare 5 -- Chapter 5. Recent trends of federated learning for smart healthcare systems -- Chapter 6. Federated learning and artificial intelligence in e-healthcare -- Chapter 7. Recent applications of convolutional neural networks in medical data analysis -- Chapter 8. Deep learning for facial skin issues detection: a study for global care with Healthcare 5 -- Chapter 9. Healthcare 5.0:intelligent lung cancer disease prediction model using blockchain-based federated learning method -- Chapter 10. AI-powered healthcare system to fight the COVID-19 pandemic on federated learning -- Chapter 11. A study and analysis on diagnosis of melanoma cancer with deep learning: a case study -- Chapter 12. Surveilance of age and gender with ML: a knowledge based statistical analysis for next gen software products -- Chapter 13. Voice and speech recognition application inemotion detection: a utility for future trends -- Chapter 14. Applications of pipelining with ML to authenticate emotions in textual contents -- Chapter 15. Ensuring hala compliance in AI-driven healthcare solutions: balancing innovation andfaith -- Chapter 16. Application domains of federated learning in Healthcare 5.0 -- Chapter 17. Generative AI and Healthcare 5.0: a revolution.

"This book explores the fundamentals of Healthcare 5.0, discuss the role of Cloud Computing in its implementation, address security and privacy concerns in Cloud-based healthcare, explore federated learning in Healthcare 5.0, provide practical insights through case studies and simulations, and examine emerging technologies and future directions that will impact the evolution of Healthcare 5.0"--

ISBN: 9798369310830$q(ebook)Subjects--Topical Terms:

194058
Artificial intelligence.
Index Terms--Genre/Form:

214472
Electronic books.

LC Class. No.: R859.7.A78 / L48 2024e

Dewey Class. No.: 610.285

National Library of Medicine Call No.: W 26.55.A7 / L48 2024e

Federated learning and AI for healthcare 5.0
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245 0 0 $a Federated learning and AI for healthcare 5.0 $h [electronic resource] / $c edited by Ahdi Hassan, Vivek Prasad, Pronaya Bhattacharya, Pushan Dutta, Robertas Damasevicius.
260 $a Hershey, Pennsylvania : $b IGI Global, $c 2024.
300 $a 1 online resource (391 p.)
504 $a Includes bibliographical references and index.
505 0 $a Chapter 1. Healthcare 5.0 fundamentals -- Chapter 2. Introduction to cloud computing and healthcare 5.0: transforming the future of healthcare -- Chapter 3. Development of personalized healthcare systems (Healthcare 5.0) and its impact on wellbeing: understanding the concepts -- Chapter 4. Intelligent biosensors for Healthcare 5 -- Chapter 5. Recent trends of federated learning for smart healthcare systems -- Chapter 6. Federated learning and artificial intelligence in e-healthcare -- Chapter 7. Recent applications of convolutional neural networks in medical data analysis -- Chapter 8. Deep learning for facial skin issues detection: a study for global care with Healthcare 5 -- Chapter 9. Healthcare 5.0:intelligent lung cancer disease prediction model using blockchain-based federated learning method -- Chapter 10. AI-powered healthcare system to fight the COVID-19 pandemic on federated learning -- Chapter 11. A study and analysis on diagnosis of melanoma cancer with deep learning: a case study -- Chapter 12. Surveilance of age and gender with ML: a knowledge based statistical analysis for next gen software products -- Chapter 13. Voice and speech recognition application inemotion detection: a utility for future trends -- Chapter 14. Applications of pipelining with ML to authenticate emotions in textual contents -- Chapter 15. Ensuring hala compliance in AI-driven healthcare solutions: balancing innovation andfaith -- Chapter 16. Application domains of federated learning in Healthcare 5.0 -- Chapter 17. Generative AI and Healthcare 5.0: a revolution.
520 3 $a "This book explores the fundamentals of Healthcare 5.0, discuss the role of Cloud Computing in its implementation, address security and privacy concerns in Cloud-based healthcare, explore federated learning in Healthcare 5.0, provide practical insights through case studies and simulations, and examine emerging technologies and future directions that will impact the evolution of Healthcare 5.0"-- $c Provided by publisher.
650 0 $a Artificial intelligence. $3 194058
650 0 $a Computer security. $3 184416
650 2 $a Machine Learning. $3 833608
650 2 $a Cloud Computing. $3 777671
650 2 $a Medical Informatics Computing. $3 501930
650 2 $a Computer Security. $3 756697
655 4 $a Electronic books. $2 local. $3 214472
700 1 $a Hassan, Ahdi, $d 1991- $3 974064
700 1 $a Prasad, Vivek, $d 1981- $3 974206
700 1 $a Bhattacharya, Pronaya. $3 974205
700 1 $a Dutta, Pushan, $d 1985- $3 974204
700 1 $a Damasevicius, Robertas. $3 700015
710 2 $a IGI Global. $3 529832
856 4 0 $u http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-1082-3