A Bayesian approach to acute coronary occlusion

In the STEMI paradigm, the disease (acute coronary occlusion) is defined and named after one element (ST elevation, without regard to the remainder of the QRST) of one imperfect test (the ECG). This leads to delayed reperfusion for patients with acute coronary occlusion whose ECGs don't meet ST...

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Published in:Journal of electrocardiology 2023-11, Vol.81, p.300-302
Main Authors: McLaren, Jesse T T, Smith, Stephen W
Format: Article
Language:English
Subjects:
Artificial Intelligence
Bayes Theorem
Coronary Occlusion
Electrocardiography
Humans
ST Elevation Myocardial Infarction
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description In the STEMI paradigm, the disease (acute coronary occlusion) is defined and named after one element (ST elevation, without regard to the remainder of the QRST) of one imperfect test (the ECG). This leads to delayed reperfusion for patients with acute coronary occlusion whose ECGs don't meet STEMI criteria. In this editorial, we elaborate on the article by Jose Nunes de Alencar Neto about applying Bayesian reasoning to ECG interpretation. The Occlusion MI (OMI) paradigm offers evidencebased advances in ECG interpretation, expert-trained artificial intelligence, and a paradigm shift that incorporates a Bayesian approach to acute coronary occlusion.
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subjects Artificial Intelligence
Bayes Theorem
Coronary Occlusion
Electrocardiography
Humans
ST Elevation Myocardial Infarction
title A Bayesian approach to acute coronary occlusion
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