Bias-reduced dental age estimation in children: Machine-learning evaluation and a novel constrained random forest adaptation of the Cameriere method.
- DOI
- 10.1016/j.forsciint.2026.112979
- Published
- 2026 Aug
- Container
- Forensic science international
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.forsciint.2026.112979,
title = {Bias-reduced dental age estimation in children: Machine-learning evaluation and a novel constrained random forest adaptation of the Cameriere method.},
author = {Parlak ME and Gümüşboğa ZŞ and Gümüşboğa E and Yılmaz M and Aydan T},
year = {2026},
journal = {Forensic science international},
doi = {10.1016/j.forsciint.2026.112979},
url = {https://doi.org/10.1016/j.forsciint.2026.112979}
}RIS
TY - JOUR TI - Bias-reduced dental age estimation in children: Machine-learning evaluation and a novel constrained random forest adaptation of the Cameriere method. AU - Parlak ME AU - Gümüşboğa ZŞ AU - Gümüşboğa E AU - Yılmaz M AU - Aydan T PY - 2026 JO - Forensic science international DO - 10.1016/j.forsciint.2026.112979 UR - https://doi.org/10.1016/j.forsciint.2026.112979 ER -
APA
ME, P., ZŞ, G., E, G., M, Y., & T, A. (2026). Bias-reduced dental age estimation in children: Machine-learning evaluation and a novel constrained random forest adaptation of the Cameriere method.. Forensic science international. https://doi.org/10.1016/j.forsciint.2026.112979
Source records
- pubmed · retrieved 2026-11-10T18:05:24.883Z