Bridging the Gap Between Artificial Intelligence Research and Clinical Practice in Cardiovascular Science: What the Clinician Needs to Know



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-.

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Item Type: Article
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