Hospital-acquired infections surveillance: The machine-learning algorithm mirrors National Healthcare Safety Network definitions

Surveillance of hospital-acquired infections (HAIs) is the foundation of infection control. Machine learning (ML) has been demonstrated to be a valuable tool for HAI surveillance. We compared manual surveillance with a supervised, semiautomated, ML method, and we explored the types of infection and...

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Bibliographic Details
Published in:	Infection control and hospital epidemiology Vol. 45; no. 5; pp. 604 - 608
Main Authors:	Lukasewicz Ferreira, Stephani Amanda, Franco Meneses, Arateus Crysham, Vaz, Tiago Andres, da Fontoura Carvalho, Otavio Luiz, Hubner Dalmora, Camila, Pressotto Vanni, Daiane, Ribeiro Berti, Isabele, Pires dos Santos, Rodrigo
Format:	Journal Article
Language:	English
Published:	New York, USA Cambridge University Press 01.05.2024
Subjects:	Accuracy Algorithms Antibiotics Artificial intelligence Automation Classification Comorbidity Coronaviruses COVID-19 Cross Infection - epidemiology Disease control Electronic health records Hospitals Humans Infection Control - methods Machine learning Methods Nosocomial infections Original Article Patient safety Pneumonia Surgical site infections Urinary tract diseases Urinary tract infections Urogenital system Variables Ventilators Brazil
ISSN:	0899-823X, 1559-6834, 1559-6834
Online Access:	Get full text
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