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

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

Abstract 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‐sens...

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Bibliographic Details
Main Authors: Anders Björkelund, Mattias Ohlsson, Jakob Lundager Forberg, Arash Mokhtari, Pontus Olsson de Capretz, Ulf Ekelund, Jonas Björk
Format: Article
Language:English
Published: Wiley 2021-04-01
Series:Journal of the American College of Emergency Physicians Open
Subjects:
AI (Artificial Intelligence)
cardiovascular epidemiology
computer assisted diagnostic techniques
diagnosis epidemiology
medical decision making
statistics and numerical data machine intelligence
Online Access:https://doi.org/10.1002/emp2.12363

Internet

https://doi.org/10.1002/emp2.12363

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