Improving preeclampsia risk prediction by modeling pregnancy trajectories from routinely collected electronic medical record data

Preeclampsia is a heterogeneous and complex disease associated with rising morbidity and mortality in pregnant women and newborns in the US. Early recognition of patients at risk is a pressing clinical need to reduce the risk of adverse outcomes. We assessed whether information routinely collected i...

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Detalles Bibliográficos
Autores principales: Li, Shilong, Wang, Zichen, Vieira, Luciana A., Zheutlin, Amanda B., Ru, Boshu, Schadt, Emilio, Wang, Pei, Copperman, Alan B., Stone, Joanne L., Gross, Susan J., Kao, Yu-Han, Lau, Yan Kwan, Dolan, Siobhan M., Schadt, Eric E., Li, Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9170686/
https://www.ncbi.nlm.nih.gov/pubmed/35668134
http://dx.doi.org/10.1038/s41746-022-00612-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9170686/
https://www.ncbi.nlm.nih.gov/pubmed/35668134
http://dx.doi.org/10.1038/s41746-022-00612-x

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