Review of Data Mining Techniques in Performance Prediction for Medical Schools

Decision-makers in the higher education sector are very concerned with predicting attrition, which has an impact on how Medical Schools select the most qualified candidates for admission. The purpose of the study is to review the literature on Data Mining (DM) techniques to minimize attrition rates in Medical Schools by enhancing the capabilities of the selection process. The major finding of this research is that applicants for medical school could be accepted using DM techniques, which offer an acceptable level of prediction accuracy. By doing so, attrition and its detrimental effects on educational institutions and students would be avoided.