Machine-Learning for Phenotyping and Prognostication of Myocardial Infarction and Injury in Suspected Acute Coronary Syndrome

Khan, Ehsan; Lambrakis, Kristina; Liao, Zhibin; Gerlach, Joey; Briffa, Tom; Cullen, Louise; J. Nelson, Adam; Verjans, Johan; P. Chew, Derek

doi:10.1016/j.jacadv.2024.101011

Public

Machine-Learning for Phenotyping and Prognostication of Myocardial Infarction and Injury in Suspected Acute Coronary Syndrome

Published in JACC Advances • Jun 19, 2024

Authors:

Ehsan Khan

Kristina Lambrakis

Zhibin Liao

Abstract

Background: Clinical work-up for suspected acute coronary syndrome (ACS) is resource intensive. Objectives: This study aimed to develop a machine learning model for digitally phenotyping myocardial injury and infarction and predict 30-day events in suspected ACS patients. Methods: Training and testi...

Subject

Acute coronary syndrome

Myocardial infarction

Medicine

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