Abstract
This chapter explores the transformative applications and multifaceted benefits of machine learning (ML) in healthcare. From enhancing diagnostic accuracy and personalizing treatment to revolutionizing drug discovery and improving operational efficiency, ML is reshaping the healthcare landscape. The chapter details the deployment of ML in disease diagnosis, risk prediction, clinical decision support, remote monitoring through wearable devices, and hospital resource management. Key ML algorithms such as supervised learning, deep learning, and natural language processing are examined along with domain-specific techniques for imaging, genomics, electronic health records, and physiological data. Further, it analyzes how ML accelerates drug discovery by enabling virtual screening, target prediction, and optimizing clinical trials. The chapter also highlights the operational gains in patient scheduling, inventory optimization, and automated administrative tasks. Ethical considerations, including data privacy, algorithmic bias, and the interpretability of ML models, are addressed to ensure responsible integration. Conclusively, this chapter emphasizes the need for interdisciplinary collaboration to fully realize the potential of ML in building a more accurate, personalized, and efficient healthcare system.