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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
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author Wiemken, Timothy L.
Rutschman, Ana Santos
author_facet Wiemken, Timothy L.
Rutschman, Ana Santos
author_sort Wiemken, Timothy L.
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description 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.
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spelling pubmed-75289052020-10-02 Methodology minute: a machine learning primer for infection prevention and control Wiemken, Timothy L. Rutschman, Ana Santos Am J Infect Control Practice Forum 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. Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. 2020-12 2020-10-01 /pmc/articles/PMC7528905/ /pubmed/33011334 http://dx.doi.org/10.1016/j.ajic.2020.09.009 Text en © 2020 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Practice Forum
Wiemken, Timothy L.
Rutschman, Ana Santos
Methodology minute: a machine learning primer for infection prevention and control
title Methodology minute: a machine learning primer for infection prevention and control
title_full Methodology minute: a machine learning primer for infection prevention and control
title_fullStr Methodology minute: a machine learning primer for infection prevention and control
title_full_unstemmed Methodology minute: a machine learning primer for infection prevention and control
title_short Methodology minute: a machine learning primer for infection prevention and control
title_sort methodology minute: a machine learning primer for infection prevention and control
topic Practice Forum
url 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
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