A Machine Learning Decision Support Tool Optimizes Whole Genome Sequencing Utilization in a Neonatal Intensive Care Unit.

Edwin F Juarez Bennet PetersonErica Sanford KobayashiSheldon GilmerLaura E TobinBrandan SchultzJerica LenbergJeanne CarrollShiyu Bai-TongNathaly M SweeneyCurtis BeebeLawrence StewartLauren OlsenJulie ReinkeElizabeth A KiernanRebecca ReimersKristen WigbyChris TackaberryMark YandellCharlotte HobbsMatthew N Bainbridge

Published in: medRxiv : the preprint server for health sciences (2024)

The Mendelian Phenotype Search Engine (MPSE), a clinical decision support tool using Natural Language Processing and Machine Learning, helped neonatologists expedite decisions to whole genome sequencing (WGS) to diagnose patients in the Neonatal Intensive Care Unit. After the MPSE was introduced, utilization of WGS increased, time to ordering WGS decreased, and WGS diagnostic yield increased.

Keyphrases

machine learning
clinical decision support
end stage renal disease
preterm infants
chronic kidney disease
ejection fraction
newly diagnosed
artificial intelligence
electronic health record
prognostic factors
big data
peritoneal dialysis
autism spectrum disorder
deep learning