Adelaide Research & Scholarship
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http://hdl.handle.net/2440/127619| Citations | ||
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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. |
| RMID: | 1000019636 |
| DOI: | 10.1016/j.jcmg.2019.10.013 |
| Appears in Collections: | Medicine publications |
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