Retinal AI Predicts Neonatal Lung Disease

AI models trained on routine ROP images identify bronchopulmonary dysplasia and pulmonary hypertension in premature infants

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Deep learning models using retinal images can predict bronchopulmonary dysplasia and pulmonary hypertension in premature infants.
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The study utilized images from the i-ROP study, focusing on infants at 34 weeks' post-menstrual age or less.
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The multimodal model combining retinal images and demographic factors outperformed models using either data type alone for bronchopulmonary dysplasia.
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For pulmonary hypertension, the imaging-only model achieved a high AUC of 0.91, indicating strong diagnostic capability.
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The findings suggest potential for retinal imaging in identifying high-risk infants for cardiopulmonary complications in clinical settings.

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