Deep learning-based prediction of cardiopulmonary disease in retinal images of premature infants.

Saved in:
Bibliographic Details
Title: Deep learning-based prediction of cardiopulmonary disease in retinal images of premature infants.
Authors: Singh P; Ophthalmology, University of Colorado School of Medicine, Aurora, CO., Kumar S; Ophthalmology, University of Colorado School of Medicine, Aurora, CO., Tyagi R; Radiology, MGH/Harvard Medical School, Charlestown, MA., Young BK; Ophthalmology, Oregon Health & Science University, Portland, OR., Jordan BK; Division of Neonatology, Department of Pediatrics, Oregon Health & Science University, Portland, OR., Scottoline B; Division of Neonatology, Department of Pediatrics, Oregon Health & Science University, Portland, OR., Evers PD; Division of Pediatric Cardiology, Department of Pediatrics, Oregon Health & Science University, Portland, OR., Ostmo S; Ophthalmology, Oregon Health & Science University, Portland, OR., Coyner AS; Ophthalmology, Oregon Health & Science University, Portland, OR., Lin WC; Ophthalmology, Oregon Health & Science University, Portland, OR., Gupta A; Radiology, MGH/Harvard Medical School, Charlestown, MA., Erdogmus D; Electrical and Computer Engineering, Northeastern University, Boston, MA., Chan RP; Ophthalmology and Visual Sciences, University of Illinois at Chicago, Chicago, IL., McCourt EA; Ophthalmology, University of Colorado School of Medicine, Aurora, CO., Barry JS; Department of Pediatrics, Section of Neonatology, University of Colorado School of Medicine, Aurora, CO., McEvoy CT; Division of Neonatology, Department of Pediatrics, Oregon Health & Science University, Portland, OR., Chiang MF; National Eye Institute, National Institutes of Health, Bethesda, MD.; National Library of Medicine, National Institutes of Health, Bethesda, MD., Campbell JP; Ophthalmology, Oregon Health & Science University, Portland, OR., Kalpathy-Cramer J; Ophthalmology, University of Colorado School of Medicine, Aurora, CO.
Source: MedRxiv : the preprint server for health sciences [medRxiv] 2025 Sep 19. Date of Electronic Publication: 2025 Sep 19.
Publication Type: Journal Article; Preprint
Journal Info: Country of Publication: United States NLM ID: 101767986 Publication Model: Electronic Cited Medium: Internet NLM ISO Abbreviation: medRxiv Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
DOI:10.1101/2025.09.18.25336004