A generalizable 29-mRNA neural-network classifier for acute bacterial and viral infections

A generalizable 29-mRNA neural-network classifier for acute bacterial and viral infections

Diagnosing acute infections based on transcriptional host response shows promise, but generalizability is wanting. Here, the authors use a co-normalization framework to train a classifier to diagnose acute infections and apply it to independent data on a targeted diagnostic platform.

Bibliographic Details
Main Authors: Michael B. Mayhew, Ljubomir Buturovic, Roland Luethy, Uros Midic, Andrew R. Moore, Jonasel A. Roque, Brian D. Shaller, Tola Asuni, David Rawling, Melissa Remmel, Kirindi Choi, James Wacker, Purvesh Khatri, Angela J. Rogers, Timothy E. Sweeney
Format: Article
Language:English
Published: Nature Publishing Group 2020-03-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-020-14975-w

Internet

https://doi.org/10.1038/s41467-020-14975-w

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