Machine learning-driven identification of the gene-expression signature associated with a persistent multiple organ dysfunction trajectory in critical illness-Reference-Cited by-同舟云学术

Machine learning-driven identification of the gene-expression signature associated with a persistent multiple organ dysfunction trajectory in critical illness

Published:2024-01 Issue: Volume:99 Page:104938
ISSN:2352-3964
Container-title:eBioMedicine
language:en
Short-container-title:eBioMedicine

Author:

Atreya Mihir R.^ORCID,Banerjee Shayantan^ORCID,Lautz Andrew J.^ORCID,Alder Matthew N.,Varisco Brian M.^ORCID,Wong Hector R.,Muszynski Jennifer A.,Hall Mark W.,Sanchez-Pinto L. Nelson,Kamaleswaran Rishikesan,Cvijanovich Natalie Z.,Fitzgerald Julie C.,Weiss Scott L.,Bigham Michael T.,Jain Parag N.,Schwarz Adam J.,Lutfi Riad,Nowak Jeffrey,Allen Geoffrey L.,Thomas Neal J.,Grunwell Jocelyn R.,Baines Torrey,Quasney Michael,Haileselassie Bereketeab,Lindsell Chris J.

Funder

National Institutes of Health

NIGMS

Publisher

Elsevier BV

Subject

General Biochemistry, Genetics and Molecular Biology,General Medicine

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5. Mortality after hospital discharge among children younger than 5 years admitted with suspected sepsis in Uganda: a prospective, multisite, observational cohort study;Wiens;Lancet Child Adolesc Health,2023

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