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Predicting atrial fibrillation in primary care using machine learning.
Hill NR, Ayoubkhani D, McEwan P, Sugrue DM, Farooqui U, Lister S, Lumley M, Bakhai A, Cohen AT, O'Neill M, Clifton D, Gordon J. Hill NR, et al. PLoS One. 2019 Nov 1;14(11):e0224582. doi: 10.1371/journal.pone.0224582. eCollection 2019. PLoS One. 2019. PMID: 31675367 Free PMC article.
[No title available]
[No authors listed] [No authors listed] PMID: 32787456
Identification of undiagnosed atrial fibrillation patients using a machine learning risk prediction algorithm and diagnostic testing (PULsE-AI): Study protocol for a randomised controlled trial.
Hill NR, Arden C, Beresford-Hulme L, Camm AJ, Clifton D, Davies DW, Farooqui U, Gordon J, Groves L, Hurst M, Lawton S, Lister S, Mallen C, Martin AC, McEwan P, Pollock KG, Rogers J, Sandler B, Sugrue DM, Cohen AT. Hill NR, et al. Contemp Clin Trials. 2020 Dec;99:106191. doi: 10.1016/j.cct.2020.106191. Epub 2020 Oct 19. Contemp Clin Trials. 2020. PMID: 33091585 Free PMC article.
Identification of undiagnosed atrial fibrillation using a machine learning risk prediction algorithm and diagnostic testing (PULsE-AI) in primary care: cost-effectiveness of a screening strategy evaluated in a randomized controlled trial in England.
Hill NR, Groves L, Dickerson C, Boyce R, Lawton S, Hurst M, Pollock KG, Sugrue DM, Lister S, Arden C, Davies DW, Martin AC, Sandler B, Gordon J, Farooqui U, Clifton D, Mallen C, Rogers J, Camm AJ, Cohen AT. Hill NR, et al. J Med Econ. 2022 Jan-Dec;25(1):974-983. doi: 10.1080/13696998.2022.2102355. J Med Econ. 2022. PMID: 35834373 Free article. Clinical Trial.
50 results