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1.
Rev Med Chil ; 149(2): 248-254, 2021 Feb.
Artigo em Espanhol | MEDLINE | ID: mdl-34479270

RESUMO

The processes associated with health care generate a large amount of information that is difficult to analyze using standard statistical procedures. In this context, disciplines such as Data Science became relevant, mainly through strategies such as Machine Learning (ML). The latter groups a series of tools whose purpose is to develop algorithms to extract information from data, whether for explanation, classification, or prediction. Despite its usefulness as support for clinical decisions, its potential in health care management has been less explored. Also, there are difficulties in understanding these types of studies. This work tries to offer a nontechnical overview of the ML concept and its advantages for health care management. It collects examples of ML applications in emergency department management.


Assuntos
Algoritmos , Aprendizado de Máquina , Serviço Hospitalar de Emergência , Humanos
2.
Rev. méd. Chile ; 149(2): 248-254, feb. 2021. ilus
Artigo em Espanhol | LILACS | ID: biblio-1389434

RESUMO

The processes associated with health care generate a large amount of information that is difficult to analyze using standard statistical procedures. In this context, disciplines such as Data Science became relevant, mainly through strategies such as Machine Learning (ML). The latter groups a series of tools whose purpose is to develop algorithms to extract information from data, whether for explanation, classification, or prediction. Despite its usefulness as support for clinical decisions, its potential in health care management has been less explored. Also, there are difficulties in understanding these types of studies. This work tries to offer a nontechnical overview of the ML concept and its advantages for health care management. It collects examples of ML applications in emergency department management.


Assuntos
Humanos , Algoritmos , Aprendizado de Máquina , Serviço Hospitalar de Emergência
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