A model to predict low birth weight infants and affecting factors using data mining techniques

Introduction: Birth weight is a reliable indication of intrauterine growth and determines the child's future physical and intellectual development. The purpose of this study was to use data mining technique in identifying accurate predictors of (low birth weight) LBW. Materials and methods: This study used secondary data from 450 medical records of newborns in the educational Hospitals affiliated to Ilam University of Medical Sciences. The birth records were reviewed from April 2015 to April 2016. The checklist used to collect data comprised of two parts: demographic and effective factors (13 factors of medical and neonatal, 4 factors of mother's lifestyle and 8 about mother factors). Data were analyzed by SPSS version 21 and WEKA software.