Artificial Intelligence in Healthcare: Revolutionizing Early Detection of Intervention in Clinical Practice

Abstract

AI changes healthcare systems by bringing AI to the clinical practice. This review article sets out the roles that AI may play in clinical practice, ranging from disease diagnosis and treatment recommendations to engaging with patients. Challenges facing AI are wide-ranging and include ethical and legal issues as well as the demand for human knowledge. The literature review shows that the applications of AI in the medical field are able to enhance the disease diagnostic process, treatment selection, and clinical laboratory testing. The large scale of datasets enables AI tools to trace patterns and offer accuracy, reduce costs, and time efficiency. It will also transform personalized medicine, tailor drug dosages, improve population health management, provide virtual assistants to healthcare, support mental health care, improve patient education, and influence patient-physician trust. Bottom line: AI will now diagnose diseases, develop tailored plans, and complement the decisions of clinicians. But responsible and effective implementation is hard as it requires overcoming the hurdles of data privacy, bias, and human expertise.