Digital Transformation and XAI in Healthcare

This book explores the pivotal role of Explainable Artificial Intelligence (XAI) in driving digital transformation within the healthcare sector, providing comprehensive insights into its applications, ethical and legal considerations, technological requirements, and future trends.

Digital Transformation and XAI in Healthcare delves into the fundamental role of XAI in transforming healthcare, addressing critical issues such as data security, ethical considerations, and the integration of XAI into existing healthcare infrastructures. By offering a comprehensive overview of the technological tools, infrastructure requirements, and legal frameworks, this book equips healthcare professionals with the knowledge to navigate the complexities of XAI applications. The book explores the future of healthcare education and the pivotal role of XAI in training the next generation of healthcare professionals. It discusses how XAI can enhance learning experiences and provide more personalized education, ensuring that future clinicians are well-equipped to utilize advanced AI technologies. It also delves into the technological tools and infrastructure required for implementing XAI, as well as data management and privacy concerns. The exploration of global collaborations and innovative projects highlights the book's unique perspective on the international impact of XAI in healthcare.

Intended for healthcare professionals, researchers, and students, this book will provide valuable insights into the future of healthcare technology. Readers will be equipped with the knowledge to harness the power of XAI, ensuring that AI systems are not only accurate but also transparent, trustworthy, and ethically sound.

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Digital Transformation and XAI in Healthcare

This book explores the pivotal role of Explainable Artificial Intelligence (XAI) in driving digital transformation within the healthcare sector, providing comprehensive insights into its applications, ethical and legal considerations, technological requirements, and future trends.

Digital Transformation and XAI in Healthcare delves into the fundamental role of XAI in transforming healthcare, addressing critical issues such as data security, ethical considerations, and the integration of XAI into existing healthcare infrastructures. By offering a comprehensive overview of the technological tools, infrastructure requirements, and legal frameworks, this book equips healthcare professionals with the knowledge to navigate the complexities of XAI applications. The book explores the future of healthcare education and the pivotal role of XAI in training the next generation of healthcare professionals. It discusses how XAI can enhance learning experiences and provide more personalized education, ensuring that future clinicians are well-equipped to utilize advanced AI technologies. It also delves into the technological tools and infrastructure required for implementing XAI, as well as data management and privacy concerns. The exploration of global collaborations and innovative projects highlights the book's unique perspective on the international impact of XAI in healthcare.

Intended for healthcare professionals, researchers, and students, this book will provide valuable insights into the future of healthcare technology. Readers will be equipped with the knowledge to harness the power of XAI, ensuring that AI systems are not only accurate but also transparent, trustworthy, and ethically sound.

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Overview

This book explores the pivotal role of Explainable Artificial Intelligence (XAI) in driving digital transformation within the healthcare sector, providing comprehensive insights into its applications, ethical and legal considerations, technological requirements, and future trends.

Digital Transformation and XAI in Healthcare delves into the fundamental role of XAI in transforming healthcare, addressing critical issues such as data security, ethical considerations, and the integration of XAI into existing healthcare infrastructures. By offering a comprehensive overview of the technological tools, infrastructure requirements, and legal frameworks, this book equips healthcare professionals with the knowledge to navigate the complexities of XAI applications. The book explores the future of healthcare education and the pivotal role of XAI in training the next generation of healthcare professionals. It discusses how XAI can enhance learning experiences and provide more personalized education, ensuring that future clinicians are well-equipped to utilize advanced AI technologies. It also delves into the technological tools and infrastructure required for implementing XAI, as well as data management and privacy concerns. The exploration of global collaborations and innovative projects highlights the book's unique perspective on the international impact of XAI in healthcare.

Intended for healthcare professionals, researchers, and students, this book will provide valuable insights into the future of healthcare technology. Readers will be equipped with the knowledge to harness the power of XAI, ensuring that AI systems are not only accurate but also transparent, trustworthy, and ethically sound.


Product Details

ISBN-13: 9781040423165
Publisher: CRC Press
Publication date: 09/29/2025
Series: Biomedical and Robotics Healthcare
Sold by: Barnes & Noble
Format: eBook
Pages: 336

About the Author

İlhan Uysal is an Assistant Professor in the Department of Information Systems and Technologies at the Bucak Zeliha Tolunay School of Applied Technology and Business Administration, ‘Burdur Mehmet Akif Ersoy University’ in Turkey. He is also the director of the Bucak Emin Gulmez Technical Science of Vocational School of the same university. Her research focuses on artificial intelligence, machine learning, drug repurposing and artificial intelligence in healthcare. He received his PhD in Computer Engineering from Suleyman Demirel University, Isparta, Turkey. He also holds a Master's degree in Electrical and Computer Engineering (English) from Antalya Bilim University, Turkey, a Bachelor's degree in Computer Systems Teaching and Computer Engineering from Süleyman Demirel University and a Bachelor's degree in Management Information Systems from Anadolu University. Before joining Burdur Mehmet Akif Ersoy University, he worked as a lecturer in Computer Science at Bayburt University for 2 years. He has many publications in science citation index journals, conference proceedings, presentations and book chapters.

Roman Rodriguez-Aguilar is a professor in the Faculty of Economic and Business Sciences of the ‘‘Universidad Panamericana’’ in Mexico. His research is on large-scale mathematical optimization, statistical learning, computational intelligence, health economics, energy economics, digital economics, and digital transformation in organizations. He received his Ph.D. at the School of Economics at the National Polytechnic Institute, Mexico. He also has a master's degree in engineering from the School of Engineering at the National University of Mexico (UNAM), a master's degree in administration and public policy from the School of Government and Public Policy at Monterrey Institute of Technology and Higher Education, a postgraduate in Applied Statistics at theResearch Institute in Applied Mathematics and Systems of the UNAM and his degree in Economics at the UNAM. Before joining Panamericana University, he worked as a specialist in economics, statistics, simulation, finance, and optimization, occupying different management positions in various public and private entities such as the Ministry of Energy, Ministry of Finance, and Ministry of Health. He has co-authored many research articles in science citation index journals, conference proceedings, presentations, and book chapters. Professor Rodrı ́guez has supervised many M.Sc. and Ph.D. Students. He is a member of the National System of Researchers Level II ofCONAHCYT in Mexico.

Jafar A. Alzubi is a professor at Al Balqa Applied University, School of Engineering, Jordan. Received Ph.D. degree in Advanced Telecommunications from Swansea University, Swansea UK (2012). Master of Science degree (Hons.) in electrical and c omputer engineering from New York Institute of Technology, New York USA (2005). And Bachelor of Science degree (Hons.) in Electrical Engineering, majoring in Electronics and Communications, from the University of Engineering and Technology, Lahore Paki stan (2001). Jafar works and research e s in a multidisciplinary environment involving Machine Learning, classifications and detection of Web scams, the Internet of Things, Wireless Sensor Networks, Network Security, and Cryptography. He has managed and directed a few projects funded by the European Union. His cumulative research experience of over ten years has resulted in publishing more than Sixty paper s in highly impacted journals. Currently, he is a senior IEEE member and serves as an editor, editorial board member, and reviewer in many prestigious journals in the computer engineering and sciences field.

Mehmet Bilen is an Assistant Professor at the Department of Computer Engineering, Faculty of Engineering and Architecture, ‘Burdur Mehmet Akif Ersoy University’ in Turkey. He is also working as the Digital Transformation Coordinator of the same university. His research interests include artificial intelligence, machine learning, optimization and bioinformatics. He received his PhD degree from Isparta Süleyman Demirel University, Department of Computer Engineering. He also holds a Master's degree in Computer Engineering from Süleyman Demirel University and a Bachelor's degree in Computer Systems Teaching from Süleyman Demirel University. Before joining Burdur Mehmet Akif Ersoy University, he worked as a lecturer in Computer Science at Gümüşhane University for 2 years. He has many publications in science citation index journals, conference proceedings, presentations and book chapters.

Table of Contents

1- Explainable Artificial Intelligence and Digital Transformation in Healthcare 2- Legal and Ethical Issues in Healthcare 3- Sectoral Applications of XAI in Healthcare 4- Technology and Infrastructure for XAI in Healthcare 5- Data Management and Privacy 6- Decision Support Systems in Healthcare: Applications, Benefits, Challenges, and Future Trends 7- Healthcare Educatıon and XAI: Future Dırectıons 8- Multinational Collaborations and Innovation 9- Investigation on deployment of XAI in Healthcare Through Augmented Analytics and Augmented Artificial Intelligence 10- Generative Artificial Intelligence and Generative Adversarial Networks(GAN) 11- Applıcatıons of Bıg Data Analytıcs ın Healthcare: Insıghts from Medıcal Tourism 12- Data Management and Integration 13- Revolutionizing Medical Care: The Role of Metaverse and NFTs in Modern Healthcare 14- The Future of XAI and Digital Transformation in Healthcare 15- Ensuring Patient Autonomy and Informed Decision-Making in AI-Driven Healthcare

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