Low-cost and scalable machine learning model for identifying children and adolescents with poor oral health using survey data: An empirical study in Portugal - Lavado, Susana; Costa, Eduardo; Sturm, Niclas F.; Tafferner, Johannes S.; Rodrigues, Octávio; Pita Barros, Pedro; Zejnilovic, Leid (PloS one, 2025)
Keywords: Adolescent; Adolescents; Algorithms; Analysis; Bias; Biology and Life Sciences; Care and treatment; Child; Children; Children & youth; Complex variables; Computer and Information Sciences; Data collection; Datasets; Demographic aspects; Dental caries; Dental Caries - epidemiology; Dental insurance; Dentists; Dependent variables; Diagnosis; Digitization; Economic aspects; Feasibility studies; Female; Food selection; Health care disparities; Health care rationing; Humans; Independent variables; Learning algorithms; Machine Learning; Male; Medical personnel; Medical screening; Medicine and Health Sciences; Methods; Oral health; Oral Health - statistics & numerical data; Oral hygiene; People and Places; Physical activity; Polls & surveys; Portugal - epidemiology; Random variables; Regression analysis; Regression models; Risk assessment; Schools; Self report; Social aspects; Social discrimination learning; Social Sciences; Students; Surveys; Surveys and Questionnaires; Teenagers; Teeth; Usability; Variables; Portugal