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.

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Detalles Bibliográficos
Autores principales: 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
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2020
Materias:
Science
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Acceso en línea:https://doaj.org/article/1514bf7fdf6d4f5db8c9b6afeda1ce2b
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https://doaj.org/article/1514bf7fdf6d4f5db8c9b6afeda1ce2b

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