| dc.contributor.author | Salmanpour, Farhad | |
| dc.contributor.author | Akpinar, Meryem | |
| dc.date.accessioned | 2025-12-28T16:39:58Z | |
| dc.date.available | 2025-12-28T16:39:58Z | |
| dc.date.issued | 2025 | |
| dc.identifier.issn | 0889-5406 | |
| dc.identifier.issn | 1097-6752 | |
| dc.identifier.uri | https://doi.org/10.1016/j.ajodo.2025.02.017 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12933/2280 | |
| dc.description.abstract | Introduction: This study evaluates the diagnostic accuracy of Chat Generative Pretrained Transformer (ChatGPT)-4.0 in determining the labiolingual position of impacted maxillary canines and identifying resorptive changes in adjacent incisors using panoramic radiographs (PRs). Methods: A retrospective analysis was conducted on 105 patients with unilaterally impacted maxillary canine, including 25 patients with root resorption in adjacent incisors. To ensure accurate classification, PRs and cone-beam computed tomography images were independently evaluated by 3 orthodontists, serving as the reference standard for assessing ChatGPT-4.0's performance. Patients were categorized into 3 groups based on canine position: palatal (n = 49), midalveolar (n = 26), and labial (n = 30). For resorption evaluation, a balanced subset of 50 PRs was selected to maintain equal group sizes. Group 1 (with resorption, n = 25) included all available patients with resorption, whereas group 2 (without resorption, n = 25) was randomly selected from 80 patients without resorption. ChatGPT-4.0 analyzed the PRs to determine the labiolingual position of impacted canines and detect resorption in adjacent incisors. The results were recorded by the first researcher. ChatGPT-4.0's performance was evaluated using accuracy, precision, recall, and F1 score for both canine localization and resorption detection. Results: The model achieved an overall accuracy of 37.1% in canine localization, with the highest sensitivity (61.2%) and precision (48.4%) observed in palatal patients. However, its performance was considerably lower for midalveolar and labial positions. In detecting resorption, the model achieved an accuracy of 46.0%, performing better in identifying the absence of resorption compared with its presence. Conclusions: ChatGPT-4.0 demonstrated insufficient accuracy in determining the labiolingual position of impacted maxillary canines and detecting resorptive changes based on PRs, indicating its unsuitability for clinical applications. (Am J Orthod Dentofacial Orthop 2025;168:220-31) | |
| dc.language.iso | en | |
| dc.publisher | Mosby-Elsevier | |
| dc.relation.ispartof | American Journal of Orthodontics And Dentofacial Orthopedics | |
| dc.rights | info:eu-repo/semantics/closedAccess | |
| dc.subject | Diagnosis | |
| dc.title | Performance of Chat Generative Pretrained Transformer-4.0 in determining labiolingual localization of maxillary impacted canine and presence of resorption in incisors through panoramic radiographs: A retrospective study | |
| dc.type | Article | |
| dc.identifier.orcid | 0000-0002-2174-7520 | |
| dc.department | Afyonkarahisar Sağlık Bilimleri Üniversitesi | |
| dc.identifier.doi | 10.1016/j.ajodo.2025.02.017 | |
| dc.identifier.volume | 168 | |
| dc.identifier.issue | 2 | |
| dc.identifier.startpage | 220 | |
| dc.identifier.endpage | 231 | |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | |
| dc.department-temp | [Salmanpour, Farhad; Akpinar, Meryem] Afyonkarahisar Hlth Sci Univ, Dept Orthodont, Ismet Inonu Cd 4, TR-03030 Afyonkarahisar, Merkez Afyonkar, Turkiye | |
| dc.identifier.pmid | 40208160 | |
| dc.identifier.scopus | 2-s2.0-105002312868 | |
| dc.identifier.scopusquality | Q1 | |
| dc.identifier.wos | WOS:001578021300012 | |
| dc.identifier.wosquality | N/A | |
| dc.indekslendigikaynak | Web of Science | |
| dc.indekslendigikaynak | Scopus | |
| dc.indekslendigikaynak | PubMed | |
| dc.snmz | KA_WoS_20251227 | |