Predicting intensive care need in women with preeclampsia using machine learning – a pilot study

Predicting intensive care need in women with preeclampsia using machine learning – a pilot study

Background Predicting severe preeclampsia with need for intensive care is challenging. To better predict high-risk pregnancies to prevent adverse outcomes such as eclampsia is still an unmet need worldwide. In this study we aimed to develop a prediction model for severe outcomes using routine biomar...

Full description

Saved in:
Bibliographic Details
Main Authors: Camilla Edvinsson, Ola Björnsson, Lena Erlandsson, Stefan R. Hansson
Format: Article
Language:English
Published: Taylor & Francis Group 2024-12-01
Series:Hypertension in Pregnancy
Subjects:
Artificial intelligence
clinical prediction model
aspartate aminotransferase
uric acid
body mass index
Online Access:https://www.tandfonline.com/doi/10.1080/10641955.2024.2312165
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items