The Healthcare sector is experiencing a change in thinking with the advent of Healthcare 5.0, bringing forth improved patient care and system efficiency. However, this transformation poses significant challenges. The growing digitization of healthcare systems raises concerns about the security and privacy of patient data, making seamless data sharing and collaboration increasingly complex tasks. Additionally, as the volume of healthcare data expands exponentially, efficient handling and analysis become vital for optimizing healthcare delivery and patient outcomes. Addressing these multifaceted issues is crucial for healthcare professionals, IT experts, data scientists, and researchers seeking to fully harness the potential of Healthcare 5.0.

Federated Learning and AI for Healthcare 5.0 presents a comprehensive solution to the pressing challenges in the digitalized healthcare industry; it dives into the principles of Healthcare 5.0 and explores practical implementation through cloud computing, data analytics, and federated learning. Readers will gain profound insights into the role of cloud computing in managing vast amounts of healthcare data, such as electronic health records and real-time analytics. Cloud-based frameworks, architectures, and relevant use cases are explored to optimize healthcare delivery and improve patient outcomes.

Federated Learning and AI for Healthcare 5.0 encourages readers to take initiative and address the security and privacy concerns of cloud-based healthcare systems. It offers invaluable strategies, including security primitives, trust-based architectures, privacy models, and compliance standards, ensuring the protection of sensitive patient data while enabling secure data sharing and collaboration within the healthcare ecosystem. In-depth exploration of federated learning in healthcare empowers professionals with a comprehensive understanding of this distributed machine learning approach, preserving data privacy during analysis. Through practical case studies and simulations, readers gain actionable insights to implement federated learning models and frameworks, bringing tangible improvements to real-world healthcare 5.0 scenarios.

The book explores emerging technologies like quantum computing, blockchain-based FL cloud services, and intelligent SaaS APIs, envisioning a future where these innovations redefine healthcare 5.0 and lead to groundbreaking advancements. Federated Learning and AI for Healthcare 5.0 serves as an indispensable resource, empowering healthcare professionals, IT experts, data scientists, and academicians to navigate the complexities of modern healthcare, leveraging innovative technologies to revolutionize patient care and system efficiency. With its comprehensive approach and practical insights, this book stands at the forefront of advancing Healthcare 5.0 into a more secure, efficient, and patient-centric era.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

Blockchain
Cloud Computing
Data Analytics
Data Privacy
Electronic Health Records (EHR)
Federated Learning
Healthcare 5.0
Information Security
Machine Learning
Patient-Centric Ecosystems
Quantum Computing
Real-Time Analytics
Simulation Tools
Trust-Based Architectures
Use Cases

Table of Contents

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Editor/Author Biographies

Ahdi Hassan has been Associate or Consulting Editor of numerous journals and also served the editorial review board from 2013- to till now. He has a number of publications and research papers published in various domains. He has given contribution with the major roles such as using modern and scientific techniques to work with sounds and meanings of words, studying the relationship between the written and spoken formats of various Asian/European languages, developing the artificial languages in coherence with modern English language, and scientifically approaching the various ancient written material to trace its origin. He teaches topics connected but not limited to communication such as English for Young Learners, English for Academic Purposes, English for Science, Technology and Engineering, English for Business and Entrepreneurship, Business Intensive Course, Applied Linguistics, interpersonal communication, verbal and nonverbal communication, cross cultural competence, language and humor, intercultural communication, culture and humor, language acquisition and language in use.

Vivek Kumar Prasad is working as an Assistant Professor at Computer Science and Engineering Department. He has more than 11 years of teaching experience. Prof Vivek received his BTech degree in Computer Science and Engineering from MITS Rayagada, Odhisa and MTech degree in Computer Science and Engineering from the MVJ College of Engineering, Bangalore. He has completed his Ph. D. from Nirma University in the field of Cloud Computing and with the following dissertation title: “SLAMMP Framework for Efficient Resource Monitoring and Prediction at an IaaS Cloud”. His research interests include Distributed Computing, Cloud Computing, Machine Learning, and Artificial Intelligence. He has many publications to his credit. He has been actively involved in the organization of various workshops in the Cloud Computing domain.

Pronaya Bhattacharya has authored 130 research papers in leading journals- IEEE-TVT, IEEE-IoTJ, IEEE-TNSE, IEEE Access, FGCS, Wiley-ETT, and top conferences-ACM MobiCom, IEEE ICC, Infocom, and CITS. He is working as reviewer of reputed SCI journals - IEEE-TII, IEEE-IoT, IEEE- Access, IEEE-Network, IJCS-Wiley, OSN, JNCA-Elsevier, MTAP, and SP-Wiley. He is awarded best paper award in ICRIC-2019, and COMS2-2021. His interests include optical communications, blockchain, and machine learning.

Pushan Kumar Dutta is an accomplished Assistant Professor Grade III in Electronics and Communication Engineering Department at ASETK, Amity University Kolkata. He completed his PhD from Jadavpur University in Kolkata in 2015, and subsequently pursued a post-doctorate with a full fellowship from Erasmus Mundus Association. During his tenure at the University of Oradea in Romania, he presented a keynote speech in Bucharest. He was then appointed Research Coordinator and Assistant Professor for a college in Kurnool, Andhra Pradesh, which was to be accredited by the National Assessment and Accreditation Council (NAAC) and the National Board of Accreditation (NBA) in India. Dr Dutta is the recipient of the Young Faculty in Engineering award from Venus International awards, Chennai in 2018. He led students to various competitions and pitching events for innovation for two years before the pandemic. He has been selected by NITI Aayog as a mentor of change in 2019 and has given multiple keynotes and conference paper presentations with the affiliation of Amity University Kolkata. Dr Dutta research interests include data mining, big data, AI, edge computing, federated learning, predictive analytics, Earthquake Precursor Study, computer hardware, sustainability, electronic devices, design thinking, industry 5.0, machine ethics and intelligent systems for biomedical applications. Dr Dutta is a prolific editor, having edited three books for publishers such as IET Press and Elsevier, and indexed more than 20 book chapters in Springer, Wiley, CRC, Apple Academic Press, Taylor and Francis. He has published over 90 articles in international and reputed journals and serves as a lead guest editor in several journals published by Bonview publisher, Metaverse, Izmirakademy, American Scientific Publishing Group, and IET. Dr Dutta is a member of the technical programming committee for various noted conferences in 2022 and 2023, including Smart Cities, Arab Science and Information, and the IEEE Region 10 HTC Conference. In 2022, he delivered a keynote speech on the role of robotics in Data Science Europe, held in Belgrade, Serbia. Dr Dutta is also a coordinator at Amity University Kolkata for sports and innovation competitions, leading students to participate in national competitions. He teaches classes on IoT, robotics, and first-year engineering, as well as PG Science level classes. He has an Indian copyright for his book titled ‘Innovative Digital Teaching and Learning for Professional Readiness’ with registration number L-118639/2022. ORCID: 0000-0002-4765-3864

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