aceDen-SOFA: Dental Student Outcome Forecasting Assistant using explainable machine learning models
Artificial intelligence (AI) and machine learning (ML) are increasingly being explored in dental education to support academic assessment and identify students at risk of poor performance. However, predictive modeling in this setting remains challenging because complex, nonlinear relationships among academic and demographic variables influence student achievement. Moreover, the value of such models lies not only in prediction but also in interpretability. This study evaluated Den-SOFA, an explainable ML framewor…
Den-SOFA predicted pass/fail on restorative dentistry exit exams with AUC-ROC 0.906 and accuracy 0.86 using 26 academic and demographic variables from 96 students.
Findings are limited to a single-institution dataset of 96 students and require external validation before operational use.
Evidence
- Peer-reviewedBMC Medical Education2026-07-16
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Truvace Impact Record TRV-2026-0259, v1: “Den-SOFA: Dental Student Outcome Forecasting Assistant using explainable machine learning models.” Truvace, 2026-07-18. /record/TRV-2026-0259 (accessed at citation time). sha256 fc1ef65517a83491…
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