AI may transform medicine. This review discusses healthcare AI and its many uses. AI affects medical research, clinical decision-making, patient care, and public health. Healthcare AI raises ethical and practical concerns. AI helps medical researchers uncover patterns in big datasets. Machine learning algorithms predict disease outcomes, identify treatment targets, and analyze complex genomic data. AI could accelerate medication discovery and boost medical research on sickness. AI could enhance clinical diagnosis and treatment. Medical images, EHRs, and genetic data can help machine learning algorithms improve clinician decisions. Radiology, pathology, and cardiology benefit from AI-based decision support systems. Algorithm transparency, data quality, and bias must be addressed for safe and ethical clinical AI application. AI can automate tasks, increase communication, and personalize therapy, changing patient care. AI chatbots and virtual assistants can help patients and improve healthcare. AI-enabled remote monitoring systems can detect early warning signs and trigger interventions in chronic disease management. AI-driven predictive analytics can identify high-risk patients for personalized therapy. AI improves disease surveillance, epidemic prediction, and response preparation. Social media, wearable devices, and EHR data can help machine learning algorithms discover and predict sickness epidemics. AI improves resource allocation, public health, and population health. Address privacy, security, and unintended consequences. Finally, AI can improve medical research, clinical decision-making, patient care, and public health. Despite challenges and ethical considerations, responsible AI deployment can improve healthcare outcomes and efficiency for patients and employees