Using Blockchain Technology in Healthcare Settings: Empowering Patients with Trustworthy Data (Analytics and AI for Healthcare)

Soufiene Ben Othman

ISBN 10: 1032774452 / ISBN 13: 9781032774459

Verlag: CRC Press, 2025

Beschreibung

Bestandsnummer des Verkäufers V9781032774459

Bibliografische Details

• Titel: Using Blockchain Technology in Healthcare Settings: Empowering Patients with Trustworthy Data (Analytics and AI for Healthcare)
• Verlag: CRC Press
• Veröffentlichungsdatum: 2025
• Sprache: Englisch
• ISBN-10: 1032774452
• ISBN-13: 9781032774459
• Bindung: Softcover
• Zustand: New

Über diesen Titel

Inhaltsangabe

This book looks at the integration of blockchain technology in healthcare settings, focusing on its potential to address security and privacy concerns of medical applications. From fragmented electronic health records (EHRs) to data breaches and interoperability issues, innovative solutions are necessary to unlock the full potential of health information and prevent the recurrence of such issues.

Blockchain offers a promising framework for addressing these challenges. Its decentralized, tamper-resistant nature holds the key to building trust and transparency in healthcare data management. By leveraging blockchain technology, secure, interoperable systems empower patients to take control of their health information while facilitating a seamless collaboration among healthcare providers. Throughout this book, the authors explore the fundamental principles of blockchain technology and its applications within the healthcare landscape. From EHRs and patient consent management to pharmaceutical supply chains and clinical research, this book examines how blockchain can drive efficiency, enhance security, and ultimately improve patient outcomes.

This book is intended for a broad audience, including healthcare professionals, patients, policymakers, and anyone interested in the intersection of technology and healthcare.

Über die Autorin bzw. den Autor

Ben Othman Soufiene is an assistant professor of computer science at the University of Gabes, Tunisia. He earned a PhD in computer science at Manouba University in 2016 for his dissertation on "Secure Data Aggregation in Wireless Sensor Networks." He earned an MS degree at Monastir University in 2012. His research interests include the Internet of Medical Things, wireless body sensor networks, wireless networks, artificial intelligence, machine learning, and big data. He has coauthored more than 110 research articles with a Google H-index of 20.

Saurav Mallik (Member, IEEE) earned a PhD at Jadavpur University, Kolkata, India, in 2017. His postgraduate studies were conducted with the Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India. He is a research scientist at the University of Arizona, USA. He previously held a postdoctoral fellow with Environmental Epigenetics, Harvard T. H. Chan School of Public Health, University of Texas Health Science Center, Houston, and with the Miller School of Medicine, University of Miami, USA. He has coauthored more than 150 research articles with a Google H-index of 20. His research interests include computational biology, bioinformatics, data mining, biostatistics, and pattern recognition.

Abdulatif Alabdulatif is an assistant professor at the School of Computer Science and Information Technology, Qassim University, Saudi Arabia. He earned a PhD in computer science at RMIT University, Australia, in 2018. He earned a BSc in computer science at Qassim University, Saudi Arabia, in 2008, and an MSc in computer science at RMIT University, Australia, in 2013. He has published more than 70 academic papers in prominent journals. His research interests include applied cryptography, cloud computing, and e-health.