Machine Learning Models to Predict Exercise Stress Test Results: Optimising the Diagnostic Test Selection Strategy and Reducing Wastage in Suspected CAD Patients

J Lu,A Ihdayhid,B Chow,J Stewart,F Sanfilippo,J Eshraghian,G Small,M Bennamoun,G Dwivedi,A Goudie

doi:10.1016/j.hlc.2022.06.522

Machine Learning Models to Predict Exercise Stress Test Results: Optimising the Diagnostic Test Selection Strategy and Reducing Wastage in Suspected CAD Patients

J Lu, A Ihdayhid + Show 8 more

https://doi.org/10.1016/j.hlc.2022.06.522

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Journal: Heart Lung and Circulation

Publication Date: Jan 1, 2022

Affiliation: Fiona Stanley Hospital, University of Ottawa, University of Western Australia

#Suspected Coronary Artery Disease Patients #Suspected Coronary Artery Disease + Show 8 more

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Abstract

Cardiac exercise stress test (EST) is a commonly used investigation in the management of patients with suspected coronary artery disease (CAD). However, up to 30% EST results are either inconclusive or non-diagnostic, which results in significant resource wastage.

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