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A novel approach to preeclampsia early prediction addressing predictive uncertainty due to missing data in clinical dataset

Crossref DOI link: https://doi.org/10.1038/s41598-025-27801-4

Published Online: 2026-02-12

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Kim, Jin Woo

Kim, Nari

Kim, Ju Yeon

Han, Hye Ji

Yang, Su Ji

Han, You Jung

Park, Hee Jin

Boo, Hye Yeon

Kwak, Dong Wook

Lee, Hyun Jung

Jung, Sang Hee

Ahn, Eun Hee

Lim, Ji Hyae

Ryu, Hyun Mee
Funding

Funding for this research was provided by:

Ministry of Health & Welfare, Republic of Korea (RS-2022-KH129953)

Ministry of Health & Welfare, Republic of Korea (RS-2022-KH129953)

Ministry of Health & Welfare, Republic of Korea (RS-2022-KH129953)

Ministry of Health & Welfare, Republic of Korea (RS-2022-KH129953)

Ministry of Health & Welfare, Republic of Korea (RS-2022-KH129953)

Ministry of Health & Welfare, Republic of Korea (RS-2022-KH129953)

Ministry of Health & Welfare, Republic of Korea (RS-2022-KH129953)

Ministry of Health & Welfare, Republic of Korea (RS-2022-KH129953)

Ministry of Health & Welfare, Republic of Korea (RS-2022-KH129953)

Ministry of Health & Welfare, Republic of Korea (RS-2022-KH129953)

Ministry of Health & Welfare, Republic of Korea (RS-2022-KH129953)

Ministry of Health & Welfare, Republic of Korea (RS-2022-KH129953)

Ministry of Health & Welfare, Republic of Korea (RS-2022-KH129953)

Ministry of Health & Welfare, Republic of Korea (RS-2022-KH129953)
License Information

Text and Data Mining valid from 2026-02-12

Accepted Manuscript valid from 2026-02-12
More Information

Article History

Received: 21 January 2025

Accepted: 5 November 2025

First Online: 12 February 2026

Declarations

:

: The authors declare no competing interests.

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