Abstract: In recent years, artificial intelligence (AI) has developed rapidly, and clinical medicine has also seen revolutionary changes. This study traces the development process of AI in clinical medicine and conducts an in-depth analysis through specific clinical application cases. It systematically explores the applications of AI in clinical medicine, including intelligent diagnosis and prognosis prediction, reforms in medical education, and optimization of the entire clinical trial process. While the widespread application of AI in clinical medicine alleviates the shortage of medical personnel and provides better services to patients, it also faces numerous challenges, such as data heterogeneity, poor interpretability of AI models, difficulties in translating AI applications to clinical practice, and data privacy concerns. To address these issues, measures such as enhancing professional expertise, establishing comprehensive policies, and strengthening interdisciplinary collaboration between medicine and engineering are needed to guide the broader implementation of AI in clinical medicine.