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Comparison of machine learning and logistic regression as predictive models for adverse maternal and neonatal outcomes of preeclampsia: A retrospective study
INTRODUCTION: Preeclampsia, one of the leading causes of maternal and fetal morbidity and mortality, demands accurate predictive models for the lack of effective treatment. Predictive models based on machine learning algorithms demonstrate promising potential, while there is a controversial discussi...
Autores principales: | Zheng, Dongying, Hao, Xinyu, Khan, Muhanmmad, Wang, Lixia, Li, Fan, Xiang, Ning, Kang, Fuli, Hamalainen, Timo, Cong, Fengyu, Song, Kedong, Qiao, Chong |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9596815/ https://www.ncbi.nlm.nih.gov/pubmed/36312231 http://dx.doi.org/10.3389/fcvm.2022.959649 |
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