<p>A machine learning-based prediction model for adverse outcomes in women with preeclampsia</p>

Young Mi  Jung; Seohyun Choi; Ji Hye  Bae; Jeesun Lee; Sun Min  Kim; Byung Jae  Kim; Dong Wook  Kwak; Chan-Wook  Park; Joong Shin  Park; Jong Kwan  Jun; Sungyoung Lee; Seung Mi Lee

doi:10.7490/f1000research.1119231.1

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Jung YM, Choi S, Bae JH et al. A machine learning-based prediction model for adverse outcomes in women with preeclampsia [version 1; not peer reviewed]. F1000Research 2022, 11:1365 (poster) (https://doi.org/10.7490/f1000research.1119231.1)

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A machine learning-based prediction model for adverse outcomes in women with preeclampsia

Young Mi Jung, Seohyun Choi, Ji Hye Bae, Jeesun Lee, Sun Min Kim, Byung Jae Kim, Dong Wook Kwak, Chan-Wook Park, Joong Shin Park, Jong Kwan Jun, Sungyoung Lee, Seung Mi Lee¹

Published 23 Nov 2022 (https://doi.org/10.7490/f1000research.1119231.1)

Author Affiliations

¹ Seoul National Untiversity College of Medicine, South Korea

Copyright © 2022 Jung YM et al. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Published 23 Nov 2022

A machine learning-based prediction model for adverse outcomes in women with preeclampsia
[version 1; not peer reviewed]

Young Mi Jung, Seohyun Choi, Ji Hye Bae, Jeesun Lee, Sun Min Kim, Byung Jae Kim, Dong Wook Kwak, Chan-Wook Park, Joong Shin Park, Jong Kwan Jun, Sungyoung Lee, Seung Mi Lee¹

Author Affiliations

¹ Seoul National Untiversity College of Medicine, South Korea

Competing Interests

No competing interests were disclosed

Keywords

preeclampsia, prediction, machine learning, ensemble model

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