Evaluation of Chat Generative Pretrained Transformer-5 and the Cameriere Method in Dental Age Estimation.
Introduction: Accurate age estimation is essential in medical and forensic practice. Dental development is among the most dependable biological indicators, and radiographic methods such as the Cameriere method have been validated across populations. Recently, vision-enabled large language models, in...
| Publicado en: | Lokman Hekim Health Sciences Vol. 6; no. 2; pp. 203 - 212 |
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| Autores principales: | , , |
| Formato: | diagnostic images research tables/charts Journal Article |
| Publicado: |
KARE Publishing
Jun2026
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=194639946&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 194639946 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 27917835 N1MV jtl: Lokman Hekim Health Sciences issn: 27917835 maglogo: N pubinfo: dt: Jun2026 vid: 6 iid: 2 pid: 62027 pub: KARE Publishing artinfo: ui: 194639946 194639946 194639946 10.14744/lhhs.2026.55522 194639946 ppf: 203 ppct: 9 formats: fmt: @attributes: type: P tig: atl: Evaluation of Chat Generative Pretrained Transformer-5 and the Cameriere Method in Dental Age Estimation. aug: au: Cömert, Hamide Özdemir, Merve Ataç, Atilla Stephan affil: Department of Pediatric Dentistry, Faculty of Dentistry, Lokman Hekim University, Ankara, Türkiye sug: subj: Artificial Intelligence, Generative Evaluation Age Determination by Teeth Methods Tooth Root Anatomy and Histology Human Male Female Child, Preschool Child Adolescence Retrospective Design Record Review Comparative Studies Methodological Research Radiography, Panoramic Methods Mandible Radiography Turkiye Software Dentists Psychosocial Factors Age Factors Sex Factors Paired T-Tests Wilcoxon Rank Sum Test Reliability Intraclass Correlation Coefficient Image Processing, Computer Assisted Dental Pulp Cavity Anatomy and Histology Descriptive Research Descriptive Statistics Data Analysis Software Child, Preschool: 2-5 years Child: 6-12 years Adolescent: 13-18 years Male Female ab: Introduction: Accurate age estimation is essential in medical and forensic practice. Dental development is among the most dependable biological indicators, and radiographic methods such as the Cameriere method have been validated across populations. Recently, vision-enabled large language models, including Chat Generative Pretrained Transformer-5 (ChatGPT-5), have attracted attention for image analysis. This study evaluated the performance of ChatGPT-5 in dental age (DA) estimation and compared its agreement with chronological age (CA) with that of the Cameriere method. Methods: This retrospective, comparative, methodological study analyzed 116 cropped panoramic radiographs of the mandibular left region from Turkish children aged 4.0-13.99 years. DA was estimated digitally using ImageJ software by two calibrated pediatric dentists applying the Cameriere method, and by ChatGPT-5 under two standardized prompting conditions (unguided and Cameriere-guided). Analyses were performed on the overall sample without sex-specific or age-specific subgroup evaluations. Agreement with CA was assessed using mean absolute error (MAE) and root mean square error (RMSE). Paired comparisons were conducted using paired t-tests or Wilcoxon signed-rank tests, depending on data distribution. Reliability was evaluated using intraclass correlation coefficients (ICC). Results: The Cameriere method demonstrated the highest accuracy and reliability (MAE=0.63 years; RMSE=0.81 years). ChatGPT-5 produced estimates that have greater variation. Performance improved when guided by the Cameriere formula, but reliability remained moderate (ICC=0.57). Discussion and Conclusion: While the Cameriere method provided more consistent age estimations, ChatGPT-5's estimates were more variable and insufficiently precise for clinical or forensic use. pubtype: Academic Journal doctype: diagnostic images research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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