Using natural language processing to generate a large-scale database of aortic stenosis with long-term follow-up: the CASPER (cogstack aortic stenosis patient electronic registry) database

J Wu; D Biswas; T Seale; D Bean; N Fairhurst; G Kaye; R Dobson; P Chowienczyk; A Shah; K O'gallagher

Journal ArticleOPEN ACCESS

Using natural language processing to generate a large-scale database of aortic stenosis with long-term follow-up: the CASPER (cogstack aortic stenosis patient electronic registry) database

Wu J
Biswas D
Seale T
et al.

European Heart Journal (2023) 44(Supplement_2)

DOI: 10.1093/eurheartj/ehad655.2952

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Abstract

Background: Aortic stenosis (AS) is one of the most common heart valve diseases in the Western World, with a prevalence of approximately 4% in patients over 70 years old. High quality observational data can provide insight into characteristics that define patient trajectories and inform the design of appropriately powered randomised trials.

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APA

Wu, J., Biswas, D., Seale, T., Bean, D., Fairhurst, N., Kaye, G., … O’gallagher, K. (2023). Using natural language processing to generate a large-scale database of aortic stenosis with long-term follow-up: the CASPER (cogstack aortic stenosis patient electronic registry) database. European Heart Journal, 44(Supplement_2). https://doi.org/10.1093/eurheartj/ehad655.2952

Using natural language processing to generate a large-scale database of aortic stenosis with long-term follow-up: the CASPER (cogstack aortic stenosis patient electronic registry) database

Abstract

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