The prediction of hypercholesterolemia as a risk factor of cardiac disease using machine learning models

Cardiac disease has become one of the major causes of death in recent years. One important risk factor of an individual having cardiac disease is hypercholesterolemia, which also contributes to other diseases, for example, cerebrovascular disease, peripheral arterial disease, and coronary heart disease. However, most cases of cardiac disease were detected late. To detect hypercholesterolemia, we built a few machine-learning models from 336 individuals consisting of several factors, for instance, gender, marital status, alcohol consumption, hypertension, and age, among others. Furthermore, we analyzed the top five factors contributing to hypercholesterolemia. Before building the models, we preprocessed all data. We compared all machine learning models using the cross-validation method. The best model showed a high accuracy score of 0.89 and an AUC score of 0.94.