Clinical Value of Machine Learning Model Based on Non-Invasive Myocardial Work Parameters and Glycolipid Metabolism Indicators for the Early Diagnosis of Coronary Heart Disease
Objective This study aims to explore the clinical value of machine learning models constructed by combining non-invasive Myocardial Work (MW) parameters and clinical glycolipid metabolism indicators for the early diagnosis of coronary heart disease (CHD). Methods A total of 183 suspected CHD patients scheduled for coro...