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Computer Vision in Healthcare Prediction, Detection and Diagnosis

   Author: creativelivenew1   |   03 January 2026   |   Comments icon: 0


Free Download Computer Vision in Healthcare
by Mallik, Saurav;Mathivanan, Sandeep Kumar;Jayagopal, Prabhu;Qin, Hong;Soufiene, Ben Othman;, Sandeep Kumar Mathivanan, Prabhu Jayagopal, Hong Qin, Ben Othman Soufiene

English | 2026 | ISBN: 1032864818 | 272 pages | True PDF EPUB | 28.23 MB


The volume explores a wide-range of applications of computer vision in the field of healthcare. Computer vision, an interdisciplinary field that combines image processing, pattern recognition, and artificial intelligence, has the potential to revolutionize healthcare by enabling automated analysis and interpretation of medical images and videos. This chapter will provide an overview of the current advancements and potential future directions of computer vision applications in healthcare. Specifically, the book examines the application of computer vision techniques in various healthcare domains, including diagnostic imaging, surgical interventions, clinical decision support, and healthcare management. It reviews the challenges and limitations in implementing computer vision systems in real-world healthcare settings and discusses potential solutions. Overall, this book aims to shed light on the current and potential applications of computer vision in healthcare. It will summarize the state-of-the-art techniques, their benefits, challenges, and implications, while also discussing potential ethical considerations. The objective is to provide healthcare professionals, researchers, and practitioners with an understanding of the transformative impact of computer vision in the healthcare sector and inspire further research and development in this exciting field. It examines the application of computer vision techniques in various healthcare domains, including diagnostic imaging, surgical interventions, clinical decision support, and healthcare management. It also reviews the challenges and shortcomings in implementing computer vision systems in real-world healthcare settings.



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