Prediction of dental caries in 12-year-old children using machine-learning algorithms

  • Yang Y
  • Kim J
  • Jeong S
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Abstract

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. Objectives: The decayed-missing-filled (DMFT) index is a representative oral health indicator. Prediction of DMFT index is an important basis for the development of public oral health care projects and strategies for caries prevention. In this study, we used data from the 2015 Korean children's oral health survey to predict DMFT index and caries risk groups using statistical techniques and four different machine-learning algorithms. Methods: DMFT prediction models were constructed using multiple linear regression and four different machine-learning algorithms: decision tree regressor, decision tree classifier (DTC), random forest regressor, and random forest classifier (RFC). Thereafter, their accuracies were compared. Results: For the DMFT predictive model, the prediction accuracy of multiple linear regression and RFC were 15.24% and 43.27%, respectively. The accuracy of DTC prediction was 2.84 times that of multiple linear regression. The important feature of the machine-learning model, which predicts DMFT index and the caries risk group, was the number of teeth with sealants. Conclusions: Using data from the 2015 Korean children's oral health survey, which is considered big data in the field of oral health survey in Korea, this study confirmed that machine-learning models are more useful than statistical models for predicting DMFT index and caries risk in 12-year-old children. Therefore, it is expected that the machine-learning model can be used to predict the DMFT score. 서 론 치아우식은 대표적인 치과질환 중의 하나로, 병원성 치면세균막 에서 발생된 산(acid)에 의해 치아법랑질과 상아질이 탈회되고, 계속 진행되면 결국 치질이 파괴될 뿐만 아니라 치아신경조직인 치수와 치 조골의 염증과 통증을 유발하여 치아를 발거하게 되는 주된 원인 중 의 하나이다. 치아우식은 아동기에 발생할 수 있는 가장 흔한 만성 질 환 중에 하나이며, 전체 생애에 걸쳐 삶의 질에 큰 영향을 미치게 되므 로 중요한 공중보건 문제이다 1,2). 우식위험치아나 우식치아를 조기에 발견한다면 간단한 예방치료와 수복치료로 해결이 가능하겠지만, 이 를 방치하여 상아질이나 치수까지 침범할 경우 광범위한 치질 삭제와 근관치료, 발치 후 보철치료와 같은 침습적이고 외과적인 처치를 받게 된다. 개개인이 본인의 구강건강에 큰 관심을 갖고 치과에 방문하여 전문가에게 정기적인 관리를 받는다면 이상적이겠지만 사회경제적 여

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Yang, Y.-H., Kim, J.-S., & Jeong, S.-H. (2020). Prediction of dental caries in 12-year-old children using machine-learning algorithms. Journal of Korean Academy of Oral Health, 44(1), 55. https://doi.org/10.11149/jkaoh.2020.44.1.55

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