Machine learning-aided risk stratification system for the prediction of coronary artery disease.

Abstract Background Machine learning (ML) may be helpful to simplify the risk stratification of coronary artery disease (CAD). The current study aims to establish a ML-aided risk stratification system to simplify the procedure of the diagnosis of CAD. Methods and Results. 5819 patients with coronary artery angiography (CAG) from July 2015 and December 2018 in our hospital, 2583 patients (aged 56 ± 11, 0.8) would suggested to perform CAG directly. Conclusion Machine learning-aided detection system with the clinical data of age, sex, history of smoking, systolic and diastolic blood pressure, total cholesterol level, low- and high-density lipoprotein, triglyceride level, glycosylated hemoglobin A1c and uric acid could be helpful for the risk stratification of prediction for the coronary artery disease.