Among Artificial Intelligence/Machine Learning Methods, Automated Gradient-Boosting Models Accurately Score Intraoral Plaque in Non-Standardized Images
Implementing automated tooth segmentation and synthetic sample generation with DL training may strengthen reliability, validity, and efficiency for clinical, research, and teledentistry applications by eliminating manual image preprocessing.
Authors
- William Santo
- Bonnie Jue
- Stuart A. Gansky (ORCID: https://orcid.org/0000-0003-3147-0884)
- Francisco Ramos‐Gomez (ORCID: https://orcid.org/0000-0002-4961-2150)
- Eric Coy
- Helen Betts
Institutions
- University of California, Los Angeles (US)
- University of California, San Francisco (US)
Publication Details
- Journal
- Journal of the California Dental Association
- Published
- 2024-11-26
- DOI
- https://doi.org/10.1080/19424396.2024.2422146
- Citations
- 1
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.35