Coronary heart disease (CHD) is one of the leading causes of death globally. Although traditional diagnostic and therapeutic methods have reached a level of maturity, clinicians continue to face challenges such as handling massive volumes of data, high inter-observer variability and the risk of missed diagnoses. In recent years, the development of artificial intelligence (AI) technology has brought revolutionary changes to the prevention, diagnosis and risk assessment of CHD. This article reviews the current status and key technologies of AI in early screening, assisted diagnosis and prognostic assessment of CHD. It focuses on analyzing the research progress of AI in each link of the clinical pathway and explores the clinical application value of AI assistance. We are aiming to provide clinicians with a comprehensive perspective. Despite the significant clinical applications of AI, challenges such as the " black box" effect of algorithms, insufficient cross-center generalization ability and difficulties in clinical implementation are remained. Therefore, medical-engineering integration and prospective multi-center trials is still needed in the future. The goal is to achieve precision medicine using AI that covers the entire lifecycle of CHD.