AI-Driven Precision Medicine: Unravelling Risk Factors And Enhancing Prevention Of Coronary Heart Disease In Diabetic Patients

Abstract

Precision Medicine (PM) aims to revolutionize healthcare by promoting individualized approaches to diagnosis, treatment, and predictive assessments. This transformation is made possible through the integration of extensive, multidimensional biological data, which includes genetic profiles, functional biomarkers, and environmental factors. Among chronic conditions, diabetes remains a major global health concern and is closely associated with vascular complications, particularly Coronary Heart Disease (CHD), a leading cause of mortality worldwide. Understanding the contributing factors behind the co-occurrence of diabetes and CHD is crucial for effective prevention and management. Diabetes significantly accelerates both the onset and progression of Cardiovascular Diseases (CVD), making CVD prevention an essential component of diabetes care. In this context, Artificial Intelligence (AI) technologies, particularly Machine Learning (ML) and Deep Learning (DL), have demonstrated exceptional potential in predicting the development of CVD in individuals with diabetes. This study, therefore, aims to identify key risk factors for coronary heart disease (CHD) among diabetic patients and explore AI-driven strategies for early detection and prevention.