Development and validation of a pre-trained language model for neonatal morbidities: a retrospective, multicentre, prognostic study.

ABSTRACT:

Background

Early identification and monitoring of neonatal morbidities are critical for timely interventions that can prevent complications, optimise resource use, and support families. Although traditional tools based on tabular data and biomarkers are beneficial, they are restricted in assessing the risk of morbidities in newborns. In this study, we developed NeonatalBERT, a pre-trained large language model (LLM) that estimates the risk of neonatal morbidities from clinical notes.

Methods

This prognostic study investigated retrospective primary and external cohorts from two different quaternary-care academic medical centres in the USA: Stanford Health Care and Beth Israel Deaconess Medical Center. NeonatalBERT was initially pre-trained on clinical notes from the primary co

SUBMITTER: Xie F 

PROVIDER: S-EPMC12748047 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature