Meeting Banner
Abstract #4117

Early Prediction of Cognitive Deficits in Very Preterm Infants using Machine Learning Algorithms

Lili He1,2 and Nehal A. Parikh1,2

1Perinatal Institute, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States, 2Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States

By school age, 30-50% of very preterm infants exhibit cognitive deficits. Unfortunately, cognitive deficits cannot be reliably diagnosed until 3 to 5 years of age. These early years are now recognized as critical for neuroplasticity when early intervention therapies can enhance infants’ ability to reach their full cognitive potential. Diffuse white matter abnormality (DWMA) is seen on term-equivalent age MRI in 50-75% of very preterm infants and is predictive of cognitive deficits. In this study, we examined features of DWMA and conducted personalized prediction in very preterm infants, soon after birth, using machine learning algorithms.

This abstract and the presentation materials are available to members only; a login is required.

Join Here