AI, machine learning, and adjudication of hemodynamically significant PDA in extremely premature infants

Letter/Communication

Open access

Danielle R Rios and Patrick J McNamara

Pediatric research

03/20/2026

DOI: 10.1038/s41390-026-04828-5

PMID: 41862666

Files and links (1)

url

https://doi.org/10.1038/s41390-026-04828-5View

Published (Version of record) Open Access

Title: Subtitle: AI, machine learning, and adjudication of hemodynamically significant PDA in extremely premature infants
Creators: Danielle R Rios - University of Iowa Stead Family Children’s Hospital
Patrick J McNamara - University of Iowa
Resource Type: Letter/Communication
Publication Details: Pediatric research
DOI: 10.1038/s41390-026-04828-5
PMID: 41862666
NLM abbreviation: Pediatr Res
ISSN: 1530-0447
eISSN: 1530-0447
Publisher: Springer Nature
Language: English
Electronic publication date: 03/20/2026
Academic Unit: Stead Family Department of Pediatrics; Neonatology
Record Identifier: 9985147076602771

1 Record Views