SARS-CoV-2 infection poses a significant risk increase for adverse pregnancy outcomes both from maternal and fetal sides. A recent publication in BMC Pregnancy and Childbirth presented a machine learning algorithm to predict this risk. This commentary will discuss potential implications and applications of this study for future global health policies.

Commentary: Predicting adverse outcomes in pregnant patients positive for SARS-CoV-2 by a machine learning approach / Salmeri, N.; Candiani, M.; Cavoretto, P. I.. - In: BMC PREGNANCY AND CHILDBIRTH. - ISSN 1471-2393. - 23:1(2023). [10.1186/s12884-023-05864-3]

Commentary: Predicting adverse outcomes in pregnant patients positive for SARS-CoV-2 by a machine learning approach

Salmeri N.
Primo
;
Candiani M.
Secondo
;
Cavoretto P. I.
Ultimo
2023-01-01

Abstract

SARS-CoV-2 infection poses a significant risk increase for adverse pregnancy outcomes both from maternal and fetal sides. A recent publication in BMC Pregnancy and Childbirth presented a machine learning algorithm to predict this risk. This commentary will discuss potential implications and applications of this study for future global health policies.
2023
Artificial intelligence
COVID-19
Machine learning
Pregnancy
SARS-CoV-2
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11768/188516
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