Postpartum Haemorrhage Risk Prediction Model Developed by Machine Learning Algorithms: A Single-Centre Retrospective Analysis of Clinical Data

Postpartum Haemorrhage Risk Prediction Model Developed by Machine Learning Algorithms: A Single-Centre Retrospective Analysis of Clinical Data

Background: Postpartum haemorrhage (PPH) is a serious complication and a cause of maternal mortality after delivery. This study used machine learning algorithms and new feature selection methods to build an efficient PPH risk prediction model and provided new ideas and reference methods for PPH risk...

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Podrobná bibliografie
Hlavní autoři: Wenhuan Wang, Chanchan Liao, Hongping Zhang, Yanjun Hu
Médium: Článek
Jazyk:English
Vydáno: IMR Press 2024-03-01
Edice:Clinical and Experimental Obstetrics & Gynecology
Témata:
postpartum haemorrhage
machine learning
risk prediction
feature selection
On-line přístup:https://www.imrpress.com/journal/CEOG/51/3/10.31083/j.ceog5103060

Internet

https://www.imrpress.com/journal/CEOG/51/3/10.31083/j.ceog5103060

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