ERP127179 PRJEB43233 Constructing Caries Risk Prediction Model 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 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 ENA-FIRST-PUBLIC 2021-02-23 ENA-LAST-UPDATE 2021-02-22