Deep learning-based automated diagnosis of temporomandibular joint anterior disc displacement and its clinical application
In summary, our deep learning models exhibited high accuracy in detecting TMJ ADD and provided interpretable, visualized predictive results. These models can be integrated with clinical examinations to enhance diagnostic precision.
Authors
- Yao Min Zhu
- Yue Yu (ORCID: https://orcid.org/0000-0003-4489-5646)
- Shu Jun Wu
Institutions
- Shenzhen University (CN)
- Stomatology Hospital (CN)
Publication Details
- Journal
- Frontiers in Physiology
- Published
- 2024-12-13
- DOI
- https://doi.org/10.3389/fphys.2024.1445258
- Citations
- 3
- Primary Topic
- Temporomandibular Joint Disorders
- Type
- article
- Field-Weighted Citation Impact
- 1.51
Funders
- Division of Mathematical Sciences