Diagnostic accuracy of generative large language artificial intelligence models for the assessment of dental crowding
The performance of ChatGPT-4o mini-, Microsoft Copilot, and Claude 3.5 Sonnet in analyzing the severity of dental crowding often did not match the evaluations made by orthodontists. Further developments in image processing algorithms of commercially available generative AI models are required prior to reliable use for dental crowding classification.
Authors
- Tanmoy Bhattacharjee (ORCID: https://orcid.org/0000-0002-2550-3136)
- Baraa Daraqel (ORCID: https://orcid.org/0000-0002-6398-8920)
- Khaled Wafaie (ORCID: https://orcid.org/0000-0001-7987-869X)
- Hisham Mohammed (ORCID: https://orcid.org/0000-0003-1201-4736)
- Sabarinath Prasad (ORCID: https://orcid.org/0000-0001-6509-2055)
- Mohamed E Basyouni
Institutions
- The University of Queensland (AU)
- Al-Quds University (PS)
- University of Benghazi (LY)
- Mohammed Bin Rashid University of Medicine and Health Sciences (AE)
Publication Details
- Journal
- BMC Oral Health
- Published
- 2025-10-08
- DOI
- https://doi.org/10.1186/s12903-025-06960-w
- Primary Topic
- Dental Radiography and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00