Evaluation of tooth development stages with deep learning-based artificial intelligence algorithm
In conclusion, utilizing a deep learning-based approach for the detection of dental development on pediatric panoramic radiographs may facilitate a precise evaluation of the chronological correlation between tooth development stages and age. This can help clinicians make treatment decisions and aid dentists in finding more accurate treatment options.
Authors
- Kaan Orhan (ORCID: https://orcid.org/0000-0001-6768-0176)
- Dilara Nil Günaçar (ORCID: https://orcid.org/0000-0002-9607-6362)
- Özer Çelik (ORCID: https://orcid.org/0000-0002-4409-3101)
- İbrahim Şevki Bayrakdar (ORCID: https://orcid.org/0000-0001-5036-9867)
- Elif Bilgir (ORCID: https://orcid.org/0000-0001-9521-4682)
- Ayça Kurt
- Fatma Yanık Şılbır
- Zeynep Yeşil
Institutions
- Ankara University (TR)
- Recep Tayyip Erdoğan University (TR)
- Eskişehir Osmangazi University (TR)
- Atatürk University (TR)
Publication Details
- Journal
- BMC Oral Health
- Published
- 2024-09-03
- DOI
- https://doi.org/10.1186/s12903-024-04786-6
- Citations
- 4
- Primary Topic
- Dental Radiography and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.97