Shipley, Emily, Joddrell, Martha, Lip, Gregory YH ORCID: 0000-0002-7566-1626 and Zheng, Yalin ORCID: 0000-0002-7873-0922
(2022)
Bridging the Gap Between Artificial Intelligence Research and Clinical Practice in Cardiovascular Science: What the Clinician Needs to Know.
Arrhythmia and Electrophysiology Review, 11 (1).
e03-.
Official URL: http://dx.doi.org/10.15420/aer.2022.07
Item Type: | Article |
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Uncontrolled Keywords: | Artificial intelligence, machine learning, cardiovascular, arrhythmia, AF, ECG, risk prediction |
Divisions: | Faculty of Health and Life Sciences Faculty of Health and Life Sciences > Institute of Life Courses and Medical Sciences |
Depositing User: | Symplectic Admin |
Date Deposited: | 25 Apr 2022 08:19 |
Last Modified: | 18 Jan 2023 21:04 |
DOI: | 10.15420/aer.2022.07 |
Open Access URL: | https://doi.org/10.15420/aer.2022.07 |
Related URLs: | |
URI: | https://livrepository.liverpool.ac.uk/id/eprint/3153764 |
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