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Machine learning to predict risk for community-onset Staphylococcus aureus infections in children living in southeastern United States.

Authors :
Xiting Lin
Ruijin Geng
Kurt Menke
Mike Edelson
Fengxia Yan
Traci Leong
George S Rust
Lance A Waller
Erica L Johnson
Lilly Cheng Immergluck
Source :
PLoS ONE, Vol 18, Iss 9, p e0290375 (2023)
Publication Year :
2023
Publisher :
Public Library of Science (PLoS), 2023.

Abstract

Staphylococcus aureus (S. aureus) is known to cause human infections and since the late 1990s, community-onset antibiotic resistant infections (methicillin resistant S. aureus (MRSA)) continue to cause significant infections in the United States. Skin and soft tissue infections (SSTIs) still account for the majority of these in the outpatient setting. Machine learning can predict the location-based risks for community-level S. aureus infections. Multi-year (2002-2016) electronic health records of children

Subjects

Subjects :
Medicine
Science

Details

Language :
English
ISSN :
19326203
Volume :
18
Issue :
9
Database :
Directory of Open Access Journals
Journal :
PLoS ONE
Publication Type :
Academic Journal
Accession number :
edsdoj.6dc7543877284de2a56d71868c8d322c
Document Type :
article
Full Text :
https://doi.org/10.1371/journal.pone.0290375&type=printable