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...

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Detalles Bibliográficos
Autores principales: Zheng, Dongying, Hao, Xinyu, Khan, Muhanmmad, Wang, Lixia, Li, Fan, Xiang, Ning, Kang, Fuli, Hamalainen, Timo, Cong, Fengyu, Song, Kedong, Qiao, Chong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Cardiovascular Medicine
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

Internet

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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