Language function following preterm birth: prediction using machine learning.

ABSTRACT:

Background

Preterm birth can lead to impaired language development. This study aimed to predict language outcomes at 2 years corrected gestational age (CGA) for children born preterm.

Methods

We analysed data from 89 preterm neonates (median GA 29 weeks) who underwent diffusion MRI (dMRI) at term-equivalent age and language assessment at 2 years CGA using the Bayley-III. Feature selection and a random forests classifier were used to differentiate typical versus delayed (Bayley-III language composite score <85) language development.

Results

The model achieved balanced accuracy: 91%, sensitivity: 86%, and specificity: 96%. The probability of language delay at 2 years CGA is increased with: increasing values of peak width of skeletonized fractional anisotropy (PSFA), rad

SUBMITTER: Valavani E 

PROVIDER: S-EPMC8503721 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature