Enhancing graduate education assessment: a machine learning-based classification of academic performance in medical students

This study presents an interpretable machine learning framework for predicting academic performance in medical postgraduate education. By combining predictive modeling with explainable techniques, the proposed approach supports reliable performance assessment while maintaining transparency, offering a methodological foundation for future research and cautious application in educational analytics.