Prediction Models for Late-Onset Preeclampsia: A Study Based on Logistic Regression, Support Vector Machine, and Extreme Gradient Boosting Models
<b>Background:</b> Preeclampsia, affecting 2–4% of pregnancies worldwide, poses a substantial risk to maternal health. Late-onset preeclampsia, in particular, has a high incidence among preeclampsia cases. However, existing prediction models are limited in terms of the early detection ca...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-02-01
|
| Series: | Biomedicines |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-9059/13/2/347 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|