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Diagnostic accuracy of ChatGPT-5 in evaluating root canal treatment and periapical pathosis on periapical radiographs
Waleed Almutairi1, Mujahid Alnasser2, Hanan Alharbi3
1Division of Endodontics, Department of Conservative Dental Sciences, College of Dentistry, Qassim University, Qassim, Saudi Arabia. wgm1410@gmail.com.
Objectives:
Artificial intelligence (AI) chatbots such as ChatGPT-5 (OpenAI) are increasingly used for dental radiograph interpretation, especially among patients seeking self-assessment. However, their diagnostic accuracy in endodontics remains unclear.
Methods:
This cross-sectional STARD-AI-compliant study analyzed 271 anonymized periapical radiographs of endodontically treated posterior teeth, classified as straightforward (n = 167) or complex (n = 104), using standardized ChatGPT-5 prompts. Diagnostic criteria included obturation length (short, adequate, long), presence of voids, and periapical pathosis. Results were compared to those of a panel of general dentists and a reference standard from endodontic specialists. Sensitivity, specificity, and accuracy were calculated using the McNemar test (p < 0.05).
Results:
ChatGPT-5 demonstrated high specificity (up to 99.3%) for normal or adequately treated findings but low sensitivity for short (13.7%) or long (0.0%) obturations, voids (9.0%-22.7%), and periapical lesions (10.5%-28.6%). Overall accuracy (54.0%-63.2%) was significantly lower than that of general dentists (76.0%-85.6%) (p < 0.001).
Conclusions:
Although ChatGPT-5 achieved high specificity, its low sensitivity and overall accuracy limit diagnostic reliability. Expert clinician oversight remains essential for accurate interpretation and treatment planning.