Identification and Prediction of Low-Birthweight Baby Outcomes and Mom Risk Factors
Document Type
Article
Abstract
Despite continued improvements in prenatal care and prenatal education, Low Birthweight (LBW) remains a major causative factor of neonatal death and long-term adverse health effects in newborns. Therefore, it is crit-ical to identify risk factors associated with LBW outcomes based on the indicators from the pre-delivery period. This study aims to develop prediction models to accurately identify LBW outcomes and associated risk factors using state-of-the-art AI methods. This study is expected to have important implications for personalized LBW early prevention programs and public health policy changes.
Digital Object Identifier (DOI)
Publication Info
Published in 2022 IEEE 10th International Conference on Healthcare Informatics (ICHI), 2022.
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APA Citation
Ren, Y., Wu, D., & Lopez-De Fede, A. (2022). Identification and prediction of low-birthweight baby outcomes and mom risk factors. 2022 IEEE 10th International Conference on Healthcare Informatics (ICHI), 01–02.https://doi.org/10.1109/ICHI54592.2022.00073