Predicting Fetal Alcohol Spectrum Disorders Using Machine Learning Techniques: Multisite Retrospective Cohort Study

• Autores principales: Sarah Soyeon Oh (Autor), Irene Kuang (Autor), Hyewon Jeong (Autor), Jin-Yeop Song (Autor), Boyu Ren (Autor), Jong Youn Moon (Autor), Eun-Cheol Park (Autor), Ichiro Kawachi (Autor)
• Formato: Libro
• Publicado: JMIR Publications, 2023-07-01T00:00:00Z.
• Materias: article
• Acceso en línea: Connect to this object online.

BackgroundFetal alcohol syndrome (FAS) is a lifelong developmental disability that occurs among individuals with prenatal alcohol exposure (PAE). With improved prediction models, FAS can be diagnosed or treated early, if not completely prevented. ObjectiveIn this study, we sought to compare differen...