Comparison Between Clinical Observation and ChatGPT-Assisted Dental Assessment in School Children
DOI:
https://doi.org/10.63682/jns.v14i32S.9621Keywords:
Dental caries, Artificial intelligence, ChatGPT, Oral health screening, Preventive dentistryAbstract
This observational cross-sectional comparative study was conducted at the Department of Community and Preventive Dentistry, Watim Dental College and Hospital, Rawalpindi, between March 2025 and September 2025, to compare the accuracy and consistency of clinical dental examinations with ChatGPT-assisted assessment in evaluating dental caries and oral hygiene among school children. Clinical oral examinations were performed on children aged 5–10 years using standard WHO oral health criteria, and the same intraoral images were analyzed using ChatGPT for caries detection and oral hygiene evaluation. The findings were compared for agreement using descriptive statistical methods. The AI-based assessment demonstrated an 87.5% agreement rate with clinical diagnosis for caries detection and 90% for oral hygiene evaluation, with minor discrepancies observed in borderline caries cases. The study concludes that ChatGPT shows promising accuracy in identifying dental caries and assessing oral hygiene, closely aligning with clinical observations, and has the potential to serve as a supportive tool in large-scale oral health screening and preventive dental programs..
Downloads
References
Schwendicke F, Samek W, Krois J. Artificial intelligence in dentistry: chances and challenges. J Dent Res. 2020;99(7):769-774. PMC+1
The use of artificial intelligence in caries detection: a review. Sensors (Basel).
2022;11(9):936. MDPI
Accuracy of artificial intelligence in caries detection: a systematic review and meta-analysis. Head Face Med. 2025;21:24. BioMed Central
Applications of AI-based deep learning models for detecting dental caries. Int J Environ Res Public Health. 2024;21(3):1892. Nature+1
Artificial intelligence for radiographic imaging detection of caries lesions: a systematic review. BMC Oral Health. 2024;24:274. BioMed Central
Diagnostic accuracy of artificial intelligence-assisted caries detection. BMC Oral Health. 2024;24:754. BioMed Central
Deep learning for caries detection: a systematic review. Dentomaxillofac Radiol.
2022;51(1):20210118. PubMed
AI applications in dental caries detection from panoramic imaging: a scoping review. Dent J (Basel). 2024;13(8):366. MDPI
Comparative analysis of deep learning algorithms for dental caries detection and prediction from radiographic images: an umbrella review. PeerJ Comput Sci. 2024;10:ecs-2371. PeerJ
Automated caries detection under dental restorations and braces using deep learning and image processing. Biosensors (Basel). 2022;12(5):533. MDPI
Artificial intelligence tools in dentistry: a systematic review on diagnostic accuracy, treatment planning and operational efficiency. Int J Environ Res Public Health. 2024;21(5):2760. PMC
Application of artificial intelligence technologies for the detection and prediction of early childhood caries: a systematic review. Appl Sci. 2025;15(3):391. SpringerLink
Detecting dental caries on oral photographs using artificial intelligence: a systematic review. Oral Dis. 2022;30(8):1765-1783. Wiley Online Library
The use of artificial intelligence in the diagnosis of carious lesions. Clin Exp Dent Res. 2023;9(4):e70004. Wiley Online Library
AI-Dentify: deep learning for proximal caries detection on bitewing X-ray— HUNT4 Oral Health Study. arXiv preprint arXiv:2310.00354. 2023. arXiv
PaXNet: dental caries detection in panoramic X-ray using ensemble transfer learning and capsule classifier. arXiv preprint arXiv:2012.13666. 2020. arXiv
Interpretable and interactive deep multiple instance learning for dental caries classification in bitewing X-rays. arXiv preprint arXiv:2112.09694. 2021. arXiv
Charting new territory: AI applications in dental caries detection. Portland State University Aging & Public Health Review. 2024. PDXScholar
Applications of AI-based deep learning models for detecting dental caries. J Neonatal Surg. 2024;13(2):1827. J Neonatal Surg
Yu Y, Zhou S, Li H, et al. Deep learning for caries detection and treatment planning in radiographic imaging. Dentomaxillofac Radiol. 2023;52(4):20220266.
Kumar V, Singh R, Gupta P. Artificial intelligence in preventive dentistry: future perspectives. J Pak Med Assoc. 2024;74(2):220-226.
Baig Q, et al. Epidemiological trends of oral health in schoolchildren. Pak Oral Dent J. 2022;42(1):45-49.
Nazir MA. Oral health-related quality of life and caries experience in children.
BMC Oral Health. 2020;20(1):90.
Peres MA, et al. Oral diseases: a global public health challenge. Lancet.
2019;394(10194):249-260.
-.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
You are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
Terms:
- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
