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Article

Automated prioritization of sick newborns for whole genome sequencing using clinical natural language processing and machine learning.

Genome medicine - 16 Mar 2023

Peterson Bennet, Hernandez Edgar Javier, Hobbs Charlotte, Malone Jenkins Sabrina, Moore Barry, Rosales Edwin, Zoucha Samuel, Sanford Erica, Bainbridge Matthew N, Frise Erwin, Oriol Albert, Brunelli Luca, Kingsmore Stephen F, Yandell Mark

Abstract excerpt

BACKGROUND: Rapidly and efficiently identifying critically ill infants for whole genome sequencing (WGS) is a costly and challenging task currently performed by scarce, highly trained experts and is a major bottleneck for application of WGS in the NICU. There is a dire need for automated means to prioritize patients for WGS. METHODS: Institutional databases of electronic health records (EHRs) are logical starting...

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Topics

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Share to Infant, Newborn
Share to Intensive Care Units, Neonatal

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Source

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Identifiers

PMID: 36927505
DOI: 10.1186/s13073-023-01166-7
PMCID: PMC10018992

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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