Artificial intelligence in patients with atrial fibrillation to manage clinical complexity and comorbidities: the ARISTOTELES project

Boriani, G orcid iconORCID: 0000-0002-9820-4815, Mei, DA, Lip, GYH orcid iconORCID: 0000-0002-7566-1626, Bonini, N, Vitolo, M, Imberti, JF, Saendig, N, Bøgsted, M, Vesteghem, C, Hose, K, Sagi, T, Johnsen, S, Eriksen, M, Nielsen, PB, Brøndum, RF, Dahl, SC, Rasmussen, TS, Ortuno, FM, Roldan, V, Rivera Caravaca, JM et al (2024) Artificial intelligence in patients with atrial fibrillation to manage clinical complexity and comorbidities: the ARISTOTELES project. European Heart Journal. ISSN 0195-668X

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Artificial Intelligence in patients with atrial fibrillation to manage clinical complexity and comorbidities the ARISTOTELES project.pdf - Accepted Version
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Additional Information: This is a pre-copyedited, author-produced version of an article accepted for publication in European Heart Journal following peer review. The version of record Giuseppe Boriani, Davide Antonio Mei, Gregory Y H Lip, the ARISTOTELES Consortium , on behalf of, Artificial intelligence in patients with atrial fibrillation to manage clinical complexity and comorbidities: the ARISTOTELES project, European Heart Journal, 2024;, ehae792, https://doi.org/10.1093/eurheartj/ehae792 is available online at: https://doi.org/10.1093/eurheartj/ehae792
Uncontrolled Keywords: 1102 Cardiorespiratory Medicine and Haematology; 1103 Clinical Sciences; Cardiovascular System & Hematology
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
Divisions: Computer Science and Mathematics
Engineering
Nursing and Advanced Practice
Publisher: Oxford University Press (OUP)
Date of acceptance: 1 November 2024
Date Deposited: 13 Dec 2024 10:20
Last Modified: 03 Jul 2025 17:00
DOI or ID number: 10.1093/eurheartj/ehae792
URI: https://researchonline.ljmu.ac.uk/id/eprint/25088
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