Using Artificial Intelligence to Optimize the Use of Cardiac Investigations in Patients With Suspected Coronary Artery Disease

J Soc Cardiovasc Angiogr Interv. 2024 Mar 26;3(3Part B):101305. doi: 10.1016/j.jscai.2024.101305. eCollection 2024 Mar.

J D Schwalm^{1

2

3}, Tej Sheth^{1

2}, Natalia Pinilla-Echeverri^{1

2}, Jeremy Petch^{1

2

4

5

6}

¹ Population Health Research Institute, McMaster University and Hamilton Health Sciences, Hamilton, Ontario, Canada.
² Department of Medicine, Division of Cardiology, McMaster University, Hamilton, Ontario, Canada.
³ Centre for Evidence-Based Implementation, Hamilton Health Sciences, Hamilton, Ontario, Canada.
⁴ Centre for Data Science and Digital Health, Hamilton Health Sciences, Hamilton, Ontario, Canada.
⁵ Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
⁶ Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada.

No abstract available

Keywords: coronary angiography; coronary artery disease; coronary computed tomographic angiography; machine learning; prediction model.