A Machine Learning Approach to Predict MRI Brain Abnormalities in Preterm Infants Using Clinical Data.

Preterm infants are prone to several neurodevelopmental impairments (NDI). Early and accurate diagnosis could cooperate in the treatment of their clinical manifestations. Clinical data from a cohort of preterm infants at the neonatal intensive care unit (NICU) of the Hospital Puerta del Mar, Cadiz, Spain, was used in this work to perform a classification task to predict abnormal magnetic resonance imaging (MRI) findings using machine learning models. The results in this analysis indicate that the best model able to predict abnormal MRI findings was the K-nearest Neighbor (KNN), with a recall of 0.80. This study represents an initial step towards developing a practical and reliable tool for predicting abnormal MRI findings in preterm infants using readily available clinical data.