Identification of undiagnosed atrial fibrillation using a machine learning risk-prediction algorithm and diagnostic testing (PULsE-AI) in primary care: a multi-centre randomized controlled trial in England

AIMS: The aim of the PULsE-AI trial was to assess the effectiveness of a machine learning risk-prediction algorithm in conjunction with diagnostic testing for identifying undiagnosed atrial fibrillation (AF) in primary care in England. METHODS AND RESULTS: Eligible participants (aged ≥30 years witho...

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Detalles Bibliográficos
Autores principales: Hill, Nathan R, Groves, Lara, Dickerson, Carissa, Ochs, Andreas, Pang, Dong, Lawton, Sarah, Hurst, Michael, Pollock, Kevin G, Sugrue, Daniel M, Tsang, Carmen, Arden, Chris, Wyn Davies, David, Martin, Anne Celine, Sandler, Belinda, Gordon, Jason, Farooqui, Usman, Clifton, David, Mallen, Christian, Rogers, Jennifer, Camm, Alan John, Cohen, Alexander T
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707963/
https://www.ncbi.nlm.nih.gov/pubmed/36713002
http://dx.doi.org/10.1093/ehjdh/ztac009

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9707963/
https://www.ncbi.nlm.nih.gov/pubmed/36713002
http://dx.doi.org/10.1093/ehjdh/ztac009

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