EVALUATING THE PREDICTIVE POWER OF DISCRIMINANT ANALYSIS FOR CORONARY HEART DISEASE RISK ASSESSMENT

Abstract

Coronary heart disease (CHD) is a major public health concern. This study evaluated the predictive power of discriminant analysis for coronary heart disease (CHD) risk assessment. Using a sample of 1300 patients, the discriminant model identified significant predictors of CHD, including demographic and clinical factors. However, the model’s performance was relatively low with an accuracy of 37.6%, specificity of 33.5%, sensitivity of 41.3%, precision of 40.8%, and F1-score of 0.410. Despite identifying key predictors, the model’s limited performance suggests that further refinement or alternative models may be necessary for accurate CHD risk assessment.