A comparative analysis of deep learning models for assisting in the diagnosis of periapical lesions in periapical radiographs
ConvNeXt significantly improved the diagnostic performance of novice dentists and reduced the time required for diagnosis, thereby enhancing clinical efficiency in both diagnosis and treatment. This model shows potential for application in dental clinics or educational institutions where experienced specialists are limited, but there is a large presence of novice, less-experienced dentists.
Authors
- Xijiao Yu (ORCID: https://orcid.org/0000-0002-9289-5520)
- Yu Shao (ORCID: https://orcid.org/0009-0003-7816-9463)
- J Z Liu (ORCID: https://orcid.org/0009-0009-0561-5032)
- Xiaodong Sun
- Xiaolan Wang (ORCID: https://orcid.org/0000-0002-3549-3680)
- Xinxuan Yi
- Kexu Pan
- Chaoran Jin
- Zhuoyang Li
Institutions
- Weifang Medical University (CN)
- Shandong University (CN)
- Jinan Stomatological Hospital (CN)
- Shandong First Medical University (CN)
Publication Details
- Journal
- BMC Oral Health
- Published
- 2025-05-26
- DOI
- https://doi.org/10.1186/s12903-025-06104-0
- Citations
- 9
- Primary Topic
- Dental Radiography and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 16.11