Machine Learning in Healthcare: Revolutionizing Clinical Decision-Making with Data Analytics

Abstract

Machine learning (ML) is reshaping healthcare through the following ways: clinical decision-making through data, diagnostic precision and tailored treatment plans. Using a wide range of data, such as electronic health records, medical imaging, genomics, and wearable devices, ML models detect the trends, forecast the disease progression, and provide optimal patient care. The applications are applicable in oncology, cardiology, neurology, and chronic disease management with large improvements in the outcomes and efficiency. Although such issues as the quality of data, the clarity of algorithms, ethics, and the ability to integrate them into clinical activities have hindered its development, new advances in the field of deep learning, real-time decision support, and collaborative models of human-AI technology make ML one of the foundations of modern medicine, building a predictive, accurate, and patient-centered future.