A machine learning decision support tool optimizes WGS utilization in a neonatal intensive care unit
Abstract 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 intro...
Saved in:
Main Authors: | Edwin F. Juarez, Bennet Peterson, Erica Sanford Kobayashi, Sheldon Gilmer, Laura E. Tobin, Brandan Schultz, Jerica Lenberg, Jeanne Carroll, Shiyu Bai-Tong, Nathaly M. Sweeney, Curtis Beebe, Lawrence Stewart, Lauren Olsen, Julie Reinke, Elizabeth A. Kiernan, Rebecca Reimers, Kristen Wigby, Chris Tackaberry, Mark Yandell, Charlotte Hobbs, Matthew N. Bainbridge |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2025-01-01
|
Series: | npj Digital Medicine |
Online Access: | https://doi.org/10.1038/s41746-025-01458-9 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Sanger validation of WGS variants
by: Arina Kopernik, et al.
Published: (2025-01-01) -
Enhancement of Streptomyces aureoverticillatus HN6 through mutagenesis for improved biocontrol of banana wilt disease: an WGS approach
by: Xiangnan Yan, et al.
Published: (2025-01-01) -
On the ability to extract MLVA profiles of Vibrio cholerae isolates from WGS data generated with Oxford Nanopore Technologies
by: Jérôme Ambroise, et al.
Published: (2025-01-01) -
Phenotypic and WGS-derived antibiotic resistance patterns of Salmonella Enteritidis isolates from retail meat and environment during 2014 to 2019 in China
by: Liya Zheng, et al.
Published: (2025-01-01) -
Precisiones al derecho de acceso a la información pública a partir del primer precedente del Tribunal de Transparencia y Acceso a la Información Pública del Perú
by: GÍLMER ALARCON REQUEJO
Published: (2022-01-01)