Artificial Intelligence (AI) is transforming healthcare by enhancing diagnostic accuracy and enabling personalized medicine. Deep learning and machine learning models have demonstrated superior performance in medical imaging, disease prediction, and patient-specific treatment optimization. Convolutional neural networks have achieved remarkable results in detecting abnormalities in radiology scans, often surpassing human-level accuracy. AI-driven genomic analysis also aids in identifying disease susceptibility, enabling precision medicine approaches. Case studies on AI's role in detecting conditions such as cancer, Alzheimer's, and cardiovascular diseases highlight its ability to improve early diagnosis and optimize therapeutic interventions. However, challenges including data privacy, model interpretability, and regulatory compliance require careful consideration. The integration of diverse patient data sources and the development of real-time monitoring systems represent promising future directions. Overall, AI has substantial potential to revolutionize healthcare by reducing diagnostic errors, personalizing treatment plans, and improving patient outcomes, particularly in resource-limited settings.