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Machine learning-based prognostic modeling of early clinical outcomes in very low birth weight infants: insights from a nationwide cohort on delivery room resuscitation, prematurity-related complications, and mortality

Crossref DOI link: https://doi.org/10.1186/s12911-026-03505-1

Published Online: 2026-04-17

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

Authors

Oh, Moon-Yeon https://orcid.org/0000-0003-1444-6495
Lee, Jae-Ho https://orcid.org/0000-0003-2619-1231
License Information

Text and Data Mining valid from 2026-04-17

Accepted Manuscript valid from 2026-04-17
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Article History

Received: 31 August 2025

Accepted: 13 April 2026

First Online: 17 April 2026

Declarations

:

: This study was conducted in accordance with the principles of the Declaration of Helsinki. The Korean Neonatal Network (KNN) registry has been approved by the Institutional Review Board (IRB) of each participating hospital, and informed consent was obtained from the parent(s) of all infants prior to enrollment. The study procedures adhered to the IRB-approved protocol and relevant guidelines. The protocol was reviewed and approved by the Institutional Review Board of Seoul St. Mary’s Hospital, The Catholic University of Korea (approval number: KC13ONMI0228).

: Not applicable.

: The authors declare no competing interests.

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