Responsible AI for Digital Health and Medical Analytics (Advances in Healthcare Information Systems and Administration) - Softcover

 
9798337309743: Responsible AI for Digital Health and Medical Analytics (Advances in Healthcare Information Systems and Administration)

Inhaltsangabe

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.

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Über die Autorinnen und Autoren

Ben Othman Soufiene is an Assistant Professor of computer science at the Applied College, King Faisal University, Saudi Arabia. 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.

Dr. Chinmay Chakraborty, received a Post-doctoral fellowship at the Federal University of Piauí, Brazil, and also visited the University of Malta in Europe and Chongqing Tech. & Business Univ., China. He is an Associate Professor of KIIT-DU, India. His main research interests include the Internet of Medical Things, AI-ML, Communication & Computing, m-Health/e-health, and Medical Imaging. Dr. Chakraborty has a strong publication record with over 250 articles in peer-reviewed international journals, conferences, and book chapters. He has secured a top 2% position among global scientists by Stanford University in both 2021-24. He has also received a Marie Skłodowska-Curie Actions Europe Fellowship Grant, Horizon 2023, and has been nominated as a "Prominent Young Researcher" at the INAE, SERB, India. He Received Prize Ideation Startup Competition at the ANRF (SERB) - INAE Conclave, 2025. He received BIT BITFAA'24 award, 2024 and nominated as AICTE-Distinguished Professional, 2025.

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