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Accuracy in Dental Medicine, A New Way to Measure Trueness and Precision

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Published on: April 29, 2014

Machine Learning Methods to Predict the Academic Performance of Pre-Clinical Dental Students Based on Pre-University

Merve Koseoglu¹, Remya Ampadi Ramachandran², Merve Botsalı¹

¹Department of Prosthodontics, Faculty of Dentistry, University of Sakarya, Sakarya, Türkiye.

International Journal of Dentistry

|June 15, 2026

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Machine learning accurately predicts dentistry students' academic performance using pre-university data. University exam scores and rankings proved more influential than demographic factors in these predictions.

Area of Science:

Educational Technology
Medical Education
Data Science in Education

Background:

Limited research exists on predicting dentistry students' academic success using machine learning (ML).
This study addresses the need for predictive models in dental education.
Focuses on utilizing pre-university information for performance forecasting.

Purpose of the Study:

To predict the academic performance of pre-clinical dentistry students.
To evaluate the efficacy of ML techniques for this prediction.
To identify key pre-university factors influencing student success.

Main Methods:

Collected data from 96 dentistry graduates, including demographics, high school GPA, and university exam scores.
Applied various ML regression techniques to predict academic performance.

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Validated models using overall preclinical scores and specific course grades as target variables.

Main Results:

University exam scores and rankings were stronger predictors than demographic variables.
ML models achieved R-squared values of 0.74 or higher for overall scores.
Models demonstrated over 70% classification accuracy for subject-specific grades.

Conclusions:

Machine learning techniques can successfully predict dentistry students' academic performance.
ML models offer valuable insights into factors affecting student achievement.
This approach can aid in early identification and support for students in dental programs.