Multimodal Deep Learning–Based Screening of Degenerative Temporomandibular Joint Disease Using <scp>2D</scp> Radiography: A Cost‐Effective and Low‐Radiation Approach
This multimodal deep learning model enables effective, low-radiation, and cost-efficient screening for TMJ DJD using widely available 2D radiographs. Combining panoramic and lateral cephalometric imaging represents a promising approach for enhancing clinical screening accuracy. Larger multicenter studies are warranted for further validation.
Authors
- Kang Li (ORCID: https://orcid.org/0000-0001-6218-5715)
- Mi Yang (ORCID: https://orcid.org/0000-0002-1975-3075)
- Yi-Xiang Wang (ORCID: https://orcid.org/0000-0002-5246-5497)
- Xin Xiong
- Liang Zhao
- Yunhao Zheng
Institutions
- Sichuan University (CN)
- West China Medical Center of Sichuan University (CN)
- HealthMedia (United States) (US)
- State Key Laboratory of Oral Diseases
Publication Details
- Journal
- Oral Diseases
- Published
- 2026-03-07
- DOI
- https://doi.org/10.1111/odi.70268
- Primary Topic
- Temporomandibular Joint Disorders
- Type
- article
- Field-Weighted Citation Impact
- 0.00