Adelaide Research & Scholarship
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https://hdl.handle.net/2440/127619
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| Type: | Journal article |
| Title: | Enhanced diagnosis of severe aortic stenosis using artificial intelligence: a proof-of-concept study of 530,871 echocardiograms |
| Author: | Playford, D. Bordin, E. Mohamad, R. Stewart, S. Strange, G. |
| Citation: | JACC: Cardiovascular Imaging, 2020; 13(4):1087-1090 |
| Publisher: | Elsevier |
| Issue Date: | 2020 |
| ISSN: | 1936-878X 1876-7591 |
| Statement of Responsibility: | David Playford, Edward Bordin, Razali Mohamad, Simon Stewart, Geoff Strange |
| Abstract: | Abstract not available |
| Keywords: | Aortic Valve Humans Aortic Valve Stenosis Diagnosis, Computer-Assisted Image Interpretation, Computer-Assisted Echocardiography Prognosis Severity of Illness Index Predictive Value of Tests Ventricular Function, Left Artificial Intelligence Databases, Factual Adult Aged Aged, 80 and over Middle Aged Female Male Hemodynamics Proof of Concept Study |
| Rights: | © 2020 by the American College of Cardiology Foundation. Published by Elsevier. |
| DOI: | 10.1016/j.jcmg.2019.10.013 |
| Published version: | http://dx.doi.org/10.1016/j.jcmg.2019.10.013 |
| Appears in Collections: | Aurora harvest 4 Medicine publications |
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