Machine learning to predict risk for community-onset Staphylococcus aureus infections in children living in southeastern United States
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...
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Veröffentlicht in: | PloS one 2023-09, Vol.18 (9), p.e0290375 |
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Hauptverfasser: | , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | 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 |
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ISSN: | 1932-6203 1932-6203 |
DOI: | 10.1371/journal.pone.0290375 |