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...

Full description

Bibliographic Details
Main Authors: Wenhuan Wang, Chanchan Liao, Hongping Zhang, Yanjun Hu
Format: Article
Language:English
Published: IMR Press 2024-03-01
Series:Clinical and Experimental Obstetrics & Gynecology
Subjects:
postpartum haemorrhage
machine learning
risk prediction
feature selection
Online Access: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

Similar Items