@article{ART003233950},
author={강유민 and 여안나 and 이수영},
title={Analysis of predictive factors for dental caries risk among adolescents using the random forest algorithm},
journal={Journal of Korean society of Dental Hygiene},
issn={2287-1705},
year={2025},
volume={25},
number={4},
pages={323-333},
doi={10.13065/jksdh.2025.25.4.5}
TY - JOUR
AU - 강유민
AU - 여안나
AU - 이수영
TI - Analysis of predictive factors for dental caries risk among adolescents using the random forest algorithm
JO - Journal of Korean society of Dental Hygiene
PY - 2025
VL - 25
IS - 4
PB - Korean Society of Dental Hygiene
SP - 323
EP - 333
SN - 2287-1705
AB - Objectives: This study aimed to predict transitions from low/moderate to high/extreme caries risk among adolescents using the random forest (RF) algorithm and identify key contributing factors following a CAMBRA-students mobile application intervention. Methods: A quasi-experimental design with post hoc analysis was applied using data from 181 students aged 10–14 years. Of these, 23 (intervention: 15; control: 8) experienced an increase in risk. The RF model, built with 500 decision trees, was trained on pre–post changes in risk factors, seven protective factors, and four disease indicators. Class imbalance was handled using Synthetic Minority Over-sampling Technique (SMOTE), and the model performance was evaluated through cross-validation based on accuracy, precision, recall, F1 score, and area under the curve (AUC). Feature importance was assessed using permutation tests (p<0.05). Results: The RF model showed strong predictive performance (AUC: intervention=95.7%; control=99.7%). The key predictors in the intervention group included ∆R1 (frequent intake of fermentable carbohydrates), ∆D4 (tooth restoration within the past year), and ∆R4 (no use of oral hygiene items). In the control group, ∆D2, ∆D3, and ∆D4 were most important Conclusions: RF modeling effectively predicted the increase in caries risk and identified distinct predictors for each group. These f indings support the use of precision-targeted caries management.
KW - Adolescent;Dental caries;Machine learning;Random forest;Risk factors
DO - 10.13065/jksdh.2025.25.4.5
ER -
강유민, 여안나 and 이수영. (2025). Analysis of predictive factors for dental caries risk among adolescents using the random forest algorithm. Journal of Korean society of Dental Hygiene, 25(4), 323-333.
강유민, 여안나 and 이수영. 2025, "Analysis of predictive factors for dental caries risk among adolescents using the random forest algorithm", Journal of Korean society of Dental Hygiene, vol.25, no.4 pp.323-333. Available from: doi:10.13065/jksdh.2025.25.4.5
강유민, 여안나, 이수영 "Analysis of predictive factors for dental caries risk among adolescents using the random forest algorithm" Journal of Korean society of Dental Hygiene 25.4 pp.323-333 (2025) : 323.
강유민, 여안나, 이수영. Analysis of predictive factors for dental caries risk among adolescents using the random forest algorithm. 2025; 25(4), 323-333. Available from: doi:10.13065/jksdh.2025.25.4.5
강유민, 여안나 and 이수영. "Analysis of predictive factors for dental caries risk among adolescents using the random forest algorithm" Journal of Korean society of Dental Hygiene 25, no.4 (2025) : 323-333.doi: 10.13065/jksdh.2025.25.4.5
강유민; 여안나; 이수영. Analysis of predictive factors for dental caries risk among adolescents using the random forest algorithm. Journal of Korean society of Dental Hygiene, 25(4), 323-333. doi: 10.13065/jksdh.2025.25.4.5
강유민; 여안나; 이수영. Analysis of predictive factors for dental caries risk among adolescents using the random forest algorithm. Journal of Korean society of Dental Hygiene. 2025; 25(4) 323-333. doi: 10.13065/jksdh.2025.25.4.5
강유민, 여안나, 이수영. Analysis of predictive factors for dental caries risk among adolescents using the random forest algorithm. 2025; 25(4), 323-333. Available from: doi:10.13065/jksdh.2025.25.4.5
강유민, 여안나 and 이수영. "Analysis of predictive factors for dental caries risk among adolescents using the random forest algorithm" Journal of Korean society of Dental Hygiene 25, no.4 (2025) : 323-333.doi: 10.13065/jksdh.2025.25.4.5
