5 Key Takeaways

• 1

  Deep learning models using retinal images can predict bronchopulmonary dysplasia and pulmonary hypertension in premature infants.

• 2

  The study utilized images from the i-ROP study, focusing on infants at 34 weeks' post-menstrual age or less.

• 3

  The multimodal model combining retinal images and demographic factors outperformed models using either data type alone for bronchopulmonary dysplasia.

• 4

  For pulmonary hypertension, the imaging-only model achieved a high AUC of 0.91, indicating strong diagnostic capability.

• 5

  The findings suggest potential for retinal imaging in identifying high-risk infants for cardiopulmonary complications in clinical settings.