Dynamic Surveillance of the Cardiovascular Risk and Identification of Treatment Responders in Type 2 Diabetes Using A Machine Learning-Based Model

The ML-CVD Primary model enables dynamic prediction of cardiovascular events, facilitating ongoing risk surveillance and identification of individual drug responses. This approach holds promise for guiding personalized cardiovascular protective therapies in patients with type 2 diabetes.