Diagnostic performance of ChatGPT-4.0 in histopathological description analysis of oral and maxillofacial lesions: a comparative study with pathologists

Abstract

Objective: To evaluate the diagnostic performance of ChatGPT-4.0 in histopathological diagnoses of oral and maxillofacial lesions and compare its performance with pathologists. Study Design: A retrospective analysis of 102 histopathological descriptions was conducted. Data, including site, age and sex, were anonymized from the General University Hospital's Department of Pathology. ChatGPT-4.0 provided diagnoses, which were categorized as correct, similar, or different compared to pathologists' diagnoses. Descriptive statistics, Chi-squared tests, correlation, and regression analyses were used to assess accuracy and the influence of age and gender. Results: ChatGPT-4.0 correctly diagnosed 61 out of 102 cases, yielding an accuracy of 59.8%. The distribution of diagnostic scores did not significantly deviate from expectations (Chi-squared Statistic: 0.0, P = 1.0). A moderate negative correlation between age and diagnostic scores (r = −0.33) was observed, with age significantly predicting scores (P = .001). No significant difference was found between genders (P = .26). ChatGPT-4.0 performed worst with granuloma and inflammation cases (100% incorrect) and best with mucocele cases (93.3% correct). Conclusion: ChatGPT-4.0 shows moderate accuracy in histopathological diagnosis of oral and maxillofacial lesions, with performance varying by lesion type. Improvements are needed to enhance its clinical reliability.