Artificial Intelligence‐Assisted Clinical Decision Model for Managing Retained Second Deciduous Molars With No Permanent Successors
The Random Forest classifier demonstrated the highest accuracy in aiding the clinical decision-making process for managing retained SDM with no permanent successors. Key factors influencing treatment decision accuracy included patient preference for restoration, mandibular arch crowding and ankylosis.
Authors
- William Tanberg
- Mohammed H. Elnagar (ORCID: https://orcid.org/0000-0002-2332-9250)
- Ozge Colak (ORCID: https://orcid.org/0000-0002-9454-1275)
- Thikriat Al‐Jewair
Institutions
- Illinois College (US)
- University of Illinois Chicago (US)
- Hanby Environmental (United States) (US)
- University at Buffalo, State University of New York (US)
Publication Details
- Journal
- Orthodontics and Craniofacial Research
- Published
- 2026-01-16
- DOI
- https://doi.org/10.1111/ocr.70100
- Primary Topic
- Orthodontics and Dentofacial Orthopedics
- Type
- article
- Field-Weighted Citation Impact
- 0.00