Machine learning compared with rule‐in/rule‐out algorithms and logistic regression to predict acute myocardial infarction based on troponin T concentrations

OBJECTIVE: Computerized decision‐support tools may improve diagnosis of acute myocardial infarction (AMI) among patients presenting with chest pain at the emergency department (ED). The primary aim was to assess the predictive accuracy of machine learning algorithms based on paired high‐sensitivity...

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Detalhes bibliográficos
Publicado no:J Am Coll Emerg Physicians Open
Main Authors: Björkelund, Anders, Ohlsson, Mattias, Lundager Forberg, Jakob, Mokhtari, Arash, Olsson de Capretz, Pontus, Ekelund, Ulf, Björk, Jonas
Formato: Artigo
Idioma:Inglês
Publicado em: John Wiley and Sons Inc. 2021
Assuntos:
Cardiology
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7984484/
https://ncbi.nlm.nih.gov/pubmed/33778804
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/emp2.12363
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