Use of artificial intelligence to study the hospitalization of women undergoing caesarean section

Abstract Objective The incidence of caesarean sections (CSs) has increased significantly in recent years, especially in developed countries. This study aimed to identify the factors that most influence the length of hospital stay (LOS) after a CS, using data from 9,900 women who underwent CS at the...

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Bibliographic Details
Published in:BMC Public Health
Main Authors: Arianna Scala, Giuseppe Bifulco, Anna Borrelli, Rosanna Egidio, Maria Triassi, Giovanni Improta
Format: Article
Language:English
Published: BMC 2025-01-01
Subjects:
Caesarean section
Machine learning
Regression model
Public health
Length of stay
Online Access:https://doi.org/10.1186/s12889-025-21530-z

Internet

https://doi.org/10.1186/s12889-025-21530-z

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