A New Model for Caries Risk Prediction in Teenagers Using a Machine Learning Algorithm Based on Environmental and Genetic Factors

This study describes the construction of a caries risk prediction model (CRPM) based on both environmental and genetic factors, using a machine learning algorithm. This CRPM included specific patient characteristics, such as SNPs, gender, and factors like the participants being the only child of the respective families, to provide an estimate of the absolute risk of a specific caries outcome. We believe that our study makes a significant contribution to the literature because the newly constructed CRPM can accurately identify a high caries-risk population

本研究基于环境与遗传双因素，结合机器学习算法构建了龋病风险预测模型（Caries Risk Prediction Model, CRPM）。该模型纳入了患者的多项特异性特征，包括单核苷酸多态性（Single Nucleotide Polymorphisms, SNPs）、性别，以及受试对象为家庭独生子女等相关影响因素，可对特定龋病转归的绝对风险进行量化评估。我们认为本研究对该领域的学术文献具有重要贡献，因本研究新构建的龋病风险预测模型能够精准识别龋病高风险人群。