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TRV-2026-0689Certified recordPeer-reviewed

Assessing the Diagnostic Performance of ChatGPT-5.0 versus Machine Learning in Orthodontics: A Comparative Analysis for Extraction Treatment Planning

To make accurate orthodontic extraction decisions, various clinical and cephalometric variables must be evaluated. This study aims to evaluate ChatGPT-5.0's performance in distinguishing orthodontic extraction decisions and to compare it with five supervised machine learning (ML) algorithms. Of 550 retrospectively evaluated orthodontic records, 30 were reserved for calibration, leaving 520 for the main analysis. The reference standard was the consensus treatment decision of three expert orthodontists with more t…

Health · The Trace — both readings · certified 2026-08-08 · v1 · article view · machine-readable

Current reading — gain

ChatGPT-5.0 achieved 75.77% accuracy and the highest sensitivity at 76.68% for orthodontic extraction decisions, performing comparably to XGBoost and significantly better than random forest, SVM, logistic regression and MLP.

Current reading — problem

ChatGPT-5.0 did not achieve the highest overall classification accuracy and had lower specificity than XGBoost, indicating it missed the top performance for correctly identifying non-extraction cases.

Evidence

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Truvace Impact Record TRV-2026-0689, v1: “Assessing the Diagnostic Performance of ChatGPT-5.0 versus Machine Learning in Orthodontics: A Comparative Analysis for Extraction Treatment Planning.” Truvace, 2026-08-08. /record/TRV-2026-0689 (accessed at citation time). sha256 211834688fdedec9…

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