Reliability of an Artificial Intelligence Software in the Detection of Approximal Caries Lesions Using Bitewing Radiographs
In conclusion, the performance of the AI software in detecting proximal caries lesions of varying depths on bitewing radiographs was found to be decent when compared to the gold standard. This AI software has the potential to serve as an effective tool to support diagnosing initial caries in bitewing images for dental practitioners.
Authors
- Vuokko Anttonen (ORCID: https://orcid.org/0000-0002-3804-1858)
- Liina Piipari (ORCID: https://orcid.org/0009-0004-1650-848X)
- Adrian Lussi (ORCID: https://orcid.org/0000-0002-0426-3364)
- Saujanya Karki (ORCID: https://orcid.org/0000-0002-3160-8137)
- Marja‐Liisa Laitala (ORCID: https://orcid.org/0000-0001-7323-9862)
- Tarja Tanner (ORCID: https://orcid.org/0000-0001-5418-4798)
Institutions
- University of Bern (CH)
- Universität Innsbruck (AT)
- Oulu University of Applied Sciences (FI)
- University of Oulu (FI)
Publication Details
- Journal
- Caries Research
- Published
- 2025-07-04
- DOI
- https://doi.org/10.1159/000547245
- Citations
- 2
- Primary Topic
- Dental Radiography and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 3.58