Evaluation of ChatGPT’s ability to detect intraosseous pathologies with panoramic radiographs

BACKGROUND: To evaluate the diagnostic performance of GPT-4 V and GPT-5 in detecting intraosseous jaw lesions on panoramic radiographs and to assess the readability of their responses. METHODS: 119 biopsy-confirmed panoramic radiographs were retrospectively analyzed. Each image was presented to both models with four standardized diagnostic questions. Unguided and region-guided prompting were compared. Information accuracy, relevance, actionability, quality, and readability (Flesch Reading Ease Score and Flesch–Kincaid Grade Level) were recorded. RESULTS: Unguided lesion detection sensitivity was low. With location guidance, lesion identification increased to 73.9% for GPT-4 V and 78.1% for GPT-5; however, diagnostic sensitivity remained limited (31.1% and 36.1%). Information accuracy, relevance, actionability, and quality scores were mostly concentrated in the lower-to-middle range (scores 2–3). No statistically significant differences were found between the models (p > 0.05). Readability analysis showed high textual complexity (mean FKGL 12.8 and 12.7). CONCLUSION: GPT-4 V and GPT-5 did not achieve clinically acceptable diagnostic sensitivity on panoramic radiographs. Further model refinement is required before diagnostic use.