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...

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Detalles Bibliográficos
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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research
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

Internet

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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