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

Improved identification of bacterial and viral infections would reduce morbidity from sepsis, reduce antibiotic overuse, and lower healthcare costs. Here, we develop a generalizable host-gene-expression-based classifier for acute bacterial and viral infections. We use training data (N = 1069) from 1...

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Bibliographic Details

Published in:	Nature communications 2020-03, Vol.11 (1), p.1177-1177, Article 1177
Main Authors:	Mayhew, Michael B, Buturovic, Ljubomir, Luethy, Roland, Midic, Uros, Moore, Andrew R, Roque, Jonasel A, Shaller, Brian D, Asuni, Tola, Rawling, David, Remmel, Melissa, Choi, Kirindi, Wacker, James, Khatri, Purvesh, Rogers, Angela J, Sweeney, Timothy E
Format:	Article
Language:	eng
Subjects:	Acute Disease - mortality Adult Aged Aged, 80 and over Antibiotics Bacteria Bacterial Infections - diagnosis Bacterial Infections - microbiology Bacterial Infections - mortality Classifiers Datasets as Topic Diagnostic systems Female Gene expression Gene Expression Profiling - methods Hospital Mortality Host-Pathogen Interactions - genetics Humans Infections Intensive Care Units - statistics & numerical data Male Middle Aged Morbidity Neural networks Neural Networks, Computer Retraining RNA, Messenger - metabolism ROC Curve Sepsis Sepsis - diagnosis Sepsis - microbiology Sepsis - mortality Support Vector Machine Transcription Viral infections Virus Diseases - diagnosis Virus Diseases - mortality Virus Diseases - virology
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