Analysis of Clinical Parameters for Onset of Cardiovascular Events through Machine Learning Algorithm

In India, Ischemic heart disease and stroke are predominant among cardiovascular diseases (CVDs) leading to mortality. They contribute more than 80% of CVD deaths. The risk parameters which include physiological, bio-chemical parameters are analysed using statistical tools. Carotid Intima Media Thickness (CIMT) is used as the significant biomarker in the analysis. R-studio is used for analysing the data recorded from 10,031 subjects. Analysis of the biomarkers clearly indicate that they are significant risk factors contributing to CVDs. Various machine learning models are used for predicting the occurrence of the disease. XGBoost algorithm performs well with an accuracy of 98.85%