Abstract: Cardiovascular disease (CVD) is the leading cause of death in China. Integrated traditional Chinese and Western Medicine (ITCWM) has unique advantages in the prevention and treatment of CVD. However, the lack of objective quantitative standards of traditional Chinese Medicine (TCM) and the challenges in the integration of heterogeneous data of TCM and western medicine restrict its standardized development. Artificial Intelligence (AI) relies on multimodal fusion, machine learning and other technologies to provide a critical path to break the above bottlenecks. We systematically sort out the adaptation logic of AI core technology and ITCWM, review the application status and research progress in this field across five dimensions of CVD risk warning, diagnosis, treatment, prognostic management, and clinical decision support, and analyze the challenges such as insufficient data standardization, poor interpretation of algorithms, and lagging clinical translation. Therefore, we propose an implementation approach centered on standardized database construction, interpretable AI research and development, and real-world clinical verification. The aim of this study is to promote the deep integration of AI with the ITCWM, build an intelligent diagnosis and treatment system of CVD with Chinese characteristics, and provide a reference for research and transformation in this field.