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

ABSTRACT:

Importance

Bronchopulmonary dysplasia (BPD) and pulmonary hypertension (PH) are leading causes of morbidity and mortality in premature infants.

Objective

To determine whether images obtained as part of retinopathy of prematurity (ROP) screening might contain features associated with BPD and PH in infants, and whether a multimodal model integrating imaging features with demographic risk factors might outperform a model based on demographic risk alone.

Design

A deep learning model was used to study retinal images collected from patients enrolled in the multi-institutional Imaging and Informatics in Retinopathy of Prematurity (i-ROP) study.

Setting

Seven neonatal intensive care units.

Participants

493 infants at risk for ROP undergoing routine ROP screening

SUBMITTER: Singh P 

PROVIDER: S-EPMC12458496 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature