Ascertaining Framingham heart failure phenotype from inpatient electronic health record data using natural language processing: a multicentre Atherosclerosis Risk in Communities (ARIC) validation study

Carlton R Moore,Anna M Kucharska-Newton,Eric Whitsel,Gerardo Heiss,Wayne Rosamand,Stephanie Haas,Saumya Jain,Harish Yadav

doi:10.1136/bmjopen-2020-047356

Ascertaining Framingham heart failure phenotype from inpatient electronic health record data using natural language processing: a multicentre Atherosclerosis Risk in Communities (ARIC) validation study

Carlton R Moore, Anna M Kucharska-Newton + Show 6 more

Open Access

https://doi.org/10.1136/bmjopen-2020-047356

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Journal: BMJ open	Publication Date: Jun 1, 2021
Citations: 9	License type: open-access

Affiliation: University of North Carolina at Chapel Hill, University North

#Atherosclerosis Risk In Communities Study #Framingham Heart Failure + Show 8 more

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Abstract

ObjectivesUsing free-text clinical notes and reports from hospitalised patients, determine the performance of natural language processing (NLP) ascertainment of Framingham heart failure (HF) criteria and phenotype.Study designA retrospective observational study...

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