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Hill, NR, Groves, L, Dickerson, C, Ochs, A, Lawton, SA ORCID: https://orcid.org/0000-0002-8909-2057, Hurst, M, Pollock, KG, Sugrue, D, Tsang, C, Arden, C, Davies, DW, Martin, AC, Sandler, B, Gordon, J, Farooqui, U, Clifton, D, Mallen, CD ORCID: https://orcid.org/0000-0002-2677-1028, Rogers, J, Camm, JA and Cohen, A (2022) Identification of undiagnosed atrial fibrillation using a machine learning risk prediction algorithm and diagnostic testing (PULsE-AI) in primary care: a multi-centre randomised controlled trial in England. European Heart Journal, 25 (1). S111 - S111.

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Item Type:	Article
Additional Information:	This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License, which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
Uncontrolled Keywords:	atrial fibrillation, machine learning, risk prediction, primary care, screening
Subjects:	R Medicine > R Medicine (General)
Divisions:	Faculty of Medicine and Health Sciences > School of Medicine
Related URLs:	Author
Depositing User:	Symplectic
Date Deposited:	14 Jun 2022 15:46
Last Modified:	14 Jun 2022 15:46
URI:	https://eprints.keele.ac.uk/id/eprint/11005

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