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Predicting adverse outcomes in pregnant patients positive for SARS-CoV-2: a machine learning approach- a retrospective cohort study
BACKGROUND: Pregnant people are particularly vulnerable to SARS-CoV-2 infection and to ensuing severe illness. Predicting adverse maternal and perinatal outcomes could aid clinicians in deciding on hospital admission and early initiation of treatment in affected individuals, streamlining the triagin...
Autores principales: | Young, Dylan, Houshmand, Bita, Tan, Chunyi Christie, Kirubarajan, Abirami, Parbhakar, Ashna, Dada, Jazleen, Whittle, Wendy, Sobel, Mara L., Gomez, Luis M., Rüdiger, Mario, Pecks, Ulrich, Oppelt, Peter, Ray, Joel G., Hobson, Sebastian R., Snelgrove, John W., D’Souza, Rohan, Kashef, Rasha, Sussman, Dafna |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10394879/ https://www.ncbi.nlm.nih.gov/pubmed/37532986 http://dx.doi.org/10.1186/s12884-023-05679-2 |
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