The convergence of emerging technologies is reshaping industries at an unprecedented pace, and healthcare is no exception. With the rapid digitization of medical records, the proliferation of connected health devices, and the growing need for secure and efficient data management, the healthcare sector faces both immense opportunities and daunting challenges. Among the most promising solutions to these challenges are blockchain technology and federated learning-two revolutionary paradigms that offer a decentralized, privacy-preserving approach to healthcare innovation.
Decentralized Healing: Transforming Healthcare with Federated Learning and Blockchain Technologies aims to serve as a comprehensive guide to understanding and implementing these transformative technologies in the healthcare ecosystem. The chapters in this book cover a diverse range of topics, from fundamental concepts and theoretical frameworks to real-world applications and case studies. Readers will gain insights into how federated learning enables collaborative artificial intelligence (AI) training while preserving patient data privacy, how blockchain ensures data integrity, security, and traceability, and how the integration of these technologies can drive innovations in electronic health records, cybersecurity, and decentralized healthcare networks. A major highlight of this book is its focus on practical applications and future trends. Whether you are a healthcare professional, blockchain/AI researcher, policymaker, or industry leader, it offers valuable knowledge and actionable insights into how decentralized approaches can empower patients, improve medical decision-making, and revolutionize global healthcare infrastructures.
This book serves as a valuable resource for anyone passionate about the future of healthcare and technology. By embracing decentralized and privacy-preserving solutions, we can pave the way for a more secure, efficient, and patient-centric healthcare system.
Let the journey towards decentralized healing begin!
Reihe
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Postgraduate and Professional Reference
Illustrationen
58 s/w Zeichnungen, 17 s/w Tabellen, 95 s/w Abbildungen, 37 s/w Photographien bzw. Rasterbilder
17 Tables, black and white; 58 Line drawings, black and white; 37 Halftones, black and white; 95 Illustrations, black and white
Maße
Höhe: 234 mm
Breite: 156 mm
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ISBN-13
978-1-032-90208-1 (9781032902081)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Sonali Dhananjay Patil (IEEE Senior Member and ACM Senior Member) is a distinguished academician and researcher with over 22 years of experience in computer engineering. She serves as the Chairperson of the IEEE Pune Blockchain Group and Coordinator for R10-level IEEE Blockchain Groups. Currently, she is a Professor and Head of the Computer Engineering Department at Pimpri Chinchwad College of Engineering (PCCoE), Savitribai Phule Pune University (SPPU), Pune, India. Dr. Patil holds a B.E. in Computer Science and Engineering, an M.E. in Computer Engineering, and a Ph.D. in Computer Engineering. She has actively contributed to research and academia by mentoring B.Tech., M.Tech., and Ph.D. scholars in the field of blockchain. She has delivered invited talks at national and international forums and served as a Tutorial Chair for IEEE Blockchain Conferences.
Prof. Amar Buchade (IEEE Senior Member) is currently Chairing the IEEE Pune Section. He is an Associate Professor at Vishwakarma Institute of Technology (VIT
Pune). He has 18+ years of teaching experience. His main research areas are distributed system, cloud computing, distributed system security, computer networks,
Internet of things, and blockchain.
Dr. Vidy Potdar serves as the Director of the Blockchain Research and Development Laboratory (BRDL) at Curtin University in Perth, Australia. At BRDL, he spearheads a dedicated team specializing in the research, development, and implementation of commercial blockchain, AI, and Internet of things (IoT) solutions for industry and governmental clients. Under Dr. Vidy's stewardship since the establishment of the Blockchain Laboratory in 2019, the team has successfully executed eight notable blockchain projects spanning diverse sectors such as agriculture, sustainability, mining, art, healthcare, supply chain, photography, and recycling in Australia.
Dr. Rajesh Ingle, Chair, IEEE Computer Society Pune Chapter, is currently CEO of Vigix Tech Pte. Ltd. He is the Former Vice Chancellor of Symbiosis and former
Dean (Academics) and Head of the Department (Computer Engineering), and a Professor at the IIIT-NR (Indian Institute of Information Technology, Naya Raipur).
Prior to his tenure at IIIT-NR, he held the position of Professor in Computer Science and Engineering at PICT (Pune Institute of Computer Technology), Savitribai Phule
Pune University, Pune, India, and served as an Adjunct Professor at Government College of Engineering Pune. Notably, Dr. Ingle has made valuable contributions
to academia, including being a Senate Member of Savitribai Phule Pune University, Head of the EDC & Business Incubation Centre, and Head of the CE Department at PICT, Pune.
Chapter 1 Recent trends for individual Virtual Healthcare Chapter 2 Securing the Future of Health: A Survey on Data Protection and Privacy Techniques in a Decentralized System Chapter 3 Integrating Blockchain and Federated Learning for Secure and Decentralized Data Management Chapter 4 Fundamentals of Blockchain and Federated Learning: Concepts, Types, and ApplicationsFundamentals of Blockchain and Federated Learning: Concepts, Types, and Applications Chapter 5 Enhancing AI Privacy and Security: The Synergy of Blockchain and Federated Learning Chapter 6 Federated Learning: Enabling Decentralized AI While Preserving Data Privacy Chapter 7 Improving Electronic Health Record Security with Blockchain: A Comprehensive Analysis of Current Innovations and Future Directions Chapter 8 Secure Federated Learning Framework for Training Deep Learning Models Chapter 9 Blockchain for Electronic Health Records: Advancements, Applications, and Future Prospects Chapter 10 Blockchain in Healthcare: Enhancing Security, Interoperability, and Efficiency Chapter 11 Revolutionizing Electronic Health Records: Blockchain for Secure and Efficient Healthcare Data Management Chapter 12 Revolutionizing Healthcare Systems with Federated Learning and Blockchain: Insights from Case Studies Chapter 13 Securing and Managing Data in Federated Learning for Healthcare Cyber-Physical Systems: A Blockchain Approach. Chapter 14 Blockchain Security in Healthcare: Ensuring Data Integrity and Privacy Chapter 15 Enhancing Security and Efficiency in Healthcare Through Decentralized and Blockchain-Based Solutions Chapter 16 Protection of data and privacy in decentralized healthcare Chapter 17 Collaborative Healthcare Networks for Medicine Chapter 18 LedgerMed Recognising the Perfect Ledger for Patient-Centric Healthcare through Blockchain Chapter 19 The Future of Healthcare Finance with Blockchain: Predictions and Trends Chapter 20 The Interoperability Challenge in Healthcare Chapter 21 Way Ahead: Decentralized Healing Based on Blockchain and Federated Learning
