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Methodology minute: a machine learning primer for infection prevention and control

The use of machine-learning and predictive modeling in infection prevention and control activities is increasing dramatically. In order for infection preventionists to make informed decisions on the performance of any particular model as well as to determine if the output of the model will be useful...

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Detalles Bibliográficos
Autores principales: Wiemken, Timothy L., Rutschman, Ana Santos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7528905/
https://www.ncbi.nlm.nih.gov/pubmed/33011334
http://dx.doi.org/10.1016/j.ajic.2020.09.009
Descripción
Sumario:The use of machine-learning and predictive modeling in infection prevention and control activities is increasing dramatically. In order for infection preventionists to make informed decisions on the performance of any particular model as well as to determine if the output of the model will be useful for their program needs, a suitable understanding of the creation and evaluation of these models is necessary. The purpose of this primer is to introduce the infection preventionist to the most commonly used machine-learning method in infection prevention: supervised learning.