A database for using machine learning and data mining techniques for coronary artery disease diagnosis.

Journal: Scientific data
Published Date: Oct 23, 2019

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.

Authors

  • R Alizadehsani
    Institute for Intelligent Systems Research and Innovation, Deakin University, Geelong, VIC 3216, Australia.
  • M Roshanzamir
    Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan, 84156-83111, Iran.
  • M Abdar
    Département d'informatique, Université du Québec à Montréal, Montréal, Québec, Canada.
  • A Beykikhoshk
    Applied Artificial Intelligence Institute, Deakin University, Geelong, Australia.
  • A Khosravi
    Institute for Intelligent Systems Research and Innovation, Deakin University, Geelong, VIC 3216, Australia.
  • M Panahiazar
    University of California San Francisco, San Francisco, CA, USA. Maryam.Panahiazar@ucsf.edu.
  • A Koohestani
    Institute for Intelligent Systems Research and Innovation, Deakin University, Geelong, VIC 3216, Australia.
  • F Khozeimeh
    Mashhad University of Medical Science, Mashhad, Iran.
  • S Nahavandi
    Institute for Intelligent Systems Research and Innovation, Deakin University, Geelong, VIC 3216, Australia.
  • N Sarrafzadegan
    Isfahan Cardiovascular Research Center, Cardiovascular Research Institute, Isfahan University of Medical Sciences, Isfahan, Iran.

Keywords

External Resources

Popular Topics
Recent Journals