Development of early prediction model for pregnancy-associated hypertension with graph-based semi-supervised learning

Development of early prediction model for pregnancy-associated hypertension with graph-based semi-supervised learning

Abstract Clinical guidelines recommend several risk factors to identify women in early pregnancy at high risk of developing pregnancy-associated hypertension. However, these variables result in low predictive accuracy. Here, we developed a prediction model for pregnancy-associated hypertension using...

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Bibliographic Details
Main Authors: Seung Mi Lee, Yonghyun Nam, Eun Saem Choi, Young Mi Jung, Vivek Sriram, Jacob S. Leiby, Ja Nam Koo, Ig Hwan Oh, Byoung Jae Kim, Sun Min Kim, Sang Youn Kim, Gyoung Min Kim, Sae Kyung Joo, Sue Shin, Errol R. Norwitz, Chan-Wook Park, Jong Kwan Jun, Won Kim, Dokyoon Kim, Joong Shin Park
Format: Article
Language:English
Published: Nature Portfolio 2022-09-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-022-15391-4

Internet

https://doi.org/10.1038/s41598-022-15391-4

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