In recent years, the healthcare industry has witnessed a rapid integration of artificial intelligence (AI) into various aspects of patient care, diagnosis, treatment, and management. The promise of improved efficiency, accuracy, and personalized healthcare has spurred the development and adoption of AI technologies. However, this rapid advancement has brought forth numerous ethical challenges, privacy concerns, and the need for responsible governance. The increasing reliance on AI in medical analytics raises questions about patient data privacy, algorithmic bias, transparency, and the overall impact on the doctor-patient relationship. The urgency to balance innovation with ethical considerations is underscored by high-profile incidents of AI system failures, biased algorithms, and potential risks to patient safety. As technology advances, further research is necessary to showcase the possibilities of AI while navigating the complexities of responsible implementation. Responsible AI for Digital Health and Medical Analytics explores the transformative potential of AI while placing a crucial emphasis on responsible and ethical practices. It decodes complex medical analytics and examines patient privacy solutions to overcome ethical challenges. This book covers topics such as blockchain, medical diagnosis and prediction, and personalized medicine, and is a useful resource for healthcare professionals, policymakers, data scientists, computer engineers, academicians, and researchers.

�ber die Autorinnen und Autoren

Ben Othman Soufiene is an Assistant Professor of computer science at the University of Gabes, Tunisia from 2016 to 2024. He received his Ph.D. degree in computer science from Manouba University in 2016 for his dissertation on “Secure data aggregation in wireless sensor networks. He also holds M.S. degrees from the Monastir University in 2012. My research interests focus on the Internet of Medical Things, Wireless Body Sensor Networks, Wireless Networks, Artificial Intelligence, Machine Learning and Big Data. Dr. Ben Othman has published more than 120 papers at reputed international journals, conferences, and book chapters. He is an Editorial Board Member in the different Journals and Conferences. He serves as an associate editor/academic editor for international journals including IEEE Access, IEEE Sensors, IEEE Internet of Things, Elsevier, Springer, Taylor & Francis, IGI, IET, Telecommunication Computing Electronics and Control, and Wiley. Dr. Ben Othman is a Technical Program Committee Member for more than a dozen of international conferences.

Chinmay Chakraborty , SMIEEE, MACM is an Associate Professor at Birla Institute of Technology, Mesra, India. He has a diverse academic and professional background with experience in various research and teaching positions. Dr. Chakraborty completed a Post-doctoral fellowship at the Federal University of Piau�, Brazil, and also visited the University of Malta in Europe. He has worked as a Sr. Lecturer at the ICFAI University in Tripura, India, and as a Research Consultant in the Coal India project at Industrial Engineering & Management, IIT Kharagpur. He has also served as the Project Coordinator of the Telecommunication Convergence Switch project under the Indo-US joint initiative. In addition, he has worked as a Network Engineer in System Administration at MISPL, India. His main research interests include the Internet of Medical Things (IoMT), AI/ML, Communication & Computing, Telemedicine, m-Health/e-health, and Medical Imaging. Dr. Chakraborty has a strong publication record with over 200 articles in peer-reviewed international journals, conferences, and book chapters. He has also authored 25+ books, obtained 6+ patents, and edited 20+ special issues in the field. His research contributions have been widely recognized, with notable metrics such as a Google h-index of 49, an i10-index of 144, a Scopus h-index of 39, and an ISI-WoS h-index of 33.

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