Abstract
This review paper examines the transformative impact of Machine Learning (ML) in the health sector, focusing on its applications, benefits, and challenges. By synthesizing current literature, we highlight how ML enhances diagnostic accuracy, personalizes treatment, optimizes operations, and improves patient outcomes. The review also addresses the challenges faced in implementing ML technologies in healthcare and suggests future research directions for better integration and utilization. This paper explores the transformative impact of Machine Learning (ML) in the healthcare sector, emphasizing its applications in diagnostics, personalized medicine, operational efficiency, and patient management. By analyzing current trends and case studies, this research highlights how ML is revolutionizing healthcare delivery and improving patient outcomes.
Published Version
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