%0 Journal Article
%T Concordance of clinician, Chat-GPT4, and ORAD diagnoses against histopathology in Odontogenic Keratocysts and tumours: a 15-Year New Zealand retrospective study.
%A Kim P
%A Seo B
%A De Silva H
%J Oral Maxillofac Surg
%V 0
%N 0
%D 2024 Jul 26
%M 39060850
暂无%R 10.1007/s10006-024-01284-5
%X <B>BACKGROUND: </B>This research aimed to investigate the concordance between clinical impressions and histopathologic diagnoses made by clinicians and artificial intelligence tools for odontogenic keratocyst (OKC) and Odontogenic tumours (OT) in a New Zealand population from 2008 to 2023.<BR><B>METHODS: </B>Histopathological records from the Oral Pathology Centre, University of Otago (2008-2023) were examined to identify OKCs and OT. Specimen referral details, histopathologic reports, and clinician differential diagnoses, as well as those provided by ORAD and Chat-GPT4, were documented. Data were analyzed using SPSS, and concordance between provisional and histopathologic diagnoses was ascertained.<BR><B>RESULTS: </B>Of the 34,225 biopsies, 302 and 321 samples were identified as OTs and OKCs. Concordance rates were 43.2% for clinicians, 45.6% for ORAD, and 41.4% for Chat-GPT4. Corresponding Kappa value against histological diagnosis were 0.23, 0.13 and 0.14. Surgeons achieved a higher concordance rate (47.7%) compared to non-surgeons (29.82%). Odds ratio of having concordant diagnosis using Chat-GPT4 and ORAD were between 1.4 and 2.8 (p < 0.05). ROC-AUC and PR-AUC were similar between the groups (Clinician 0.62/0.42, ORAD 0.58/0.28, Char-GPT4 0.63/0.37) for ameloblastoma and for OKC (Clinician 0.64/0.78, ORAD 0.66/0.77, Char-GPT4 0.60/0.71).<BR><B>CONCLUSIONS: </B>Clinicians with surgical training achieved higher concordance rate when it comes to OT and OKC. Chat-GPT4 and Bayesian approach (ORAD) have shown potential in enhancing diagnostic capabilities.