Machine Learning Models for Identifying Dental Pain in Adolescents
This study shows the potential of ML to identify dental pain in adolescents. Modest predictive performance and fairness limitations highlight the need for improvements before widespread adoption.
Authors
- Luiz Alexandre Chisini (ORCID: https://orcid.org/0000-0002-3695-0361)
- Luana Carla Salvi (ORCID: https://orcid.org/0000-0001-5809-8272)
- Luiz Felipe Pinto (ORCID: https://orcid.org/0000-0002-9888-606X)
- F Mendes
- Maximiliano Sérgio Cenci (ORCID: https://orcid.org/0000-0002-2543-6201)
- Francine dos Santos Costa
- Tatiana Pereira-Cenci
- Flávio Fernando Demarco
Institutions
- Universidade Federal do Rio de Janeiro (BR)
- Radboud University Nijmegen (NL)
- Universidade Federal de Pelotas (BR)
- Universidade de São Paulo (BR)
- Radboud University Medical Center (NL)
Publication Details
- Journal
- International Dental Journal
- Published
- 2026-03-13
- DOI
- https://doi.org/10.1016/j.identj.2026.109469
- Primary Topic
- Dental Radiography and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00