A database for using machine learning and data mining techniques for coronary artery disease diagnosis
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Updated: Jan 5, 2026

Signal Acquisition, Score Interpretation, and Economics of a Non-Invasive Point-of-Care Test for Coronary Artery Disease
Published on: August 9, 2024
R Alizadehsani1, M Roshanzamir2, M Abdar3
1Institute for Intelligent Systems Research and Innovation, Deakin University, Geelong, VIC 3216, Australia.
Abstract:
We present the coronary artery disease (CAD) database, a comprehensive resource, comprising 126 papers and 68 datasets relevant to CAD diagnosis, extracted from the scientific literature from 1992 and 2018. These data were collected to help advance research on CAD-related machine learning and data mining algorithms, and hopefully to ultimately advance clinical diagnosis and early treatment. To aid users, we have also built a web application that presents the database through various reports.
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