Large-scale identification of aortic stenosis and its severity using natural language processing on electronic health records

Large-scale identification of aortic stenosis and its severity using natural language processing on electronic health records

Background: Systematic case identification is critical to improving population health, but widely used diagnosis code–based approaches for conditions like valvular heart disease are inaccurate and lack specificity. Objective: To develop and validate natural language processing (NLP) algorithms to id...

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Bibliographic Details
Main Authors: Matthew D. Solomon, MD, PhD, Grace Tabada, MPH, Amanda Allen, Sue Hee Sung, MPH, Alan S. Go, MD
Format: Article
Language:English
Published: Elsevier 2021-06-01
Series:Cardiovascular Digital Health Journal
Subjects:
Aortic stenosis
Echocardiography
Machine learning
Population health
Quality and outcomes
Valvular heart disease
Online Access:http://www.sciencedirect.com/science/article/pii/S2666693621000256

Internet

http://www.sciencedirect.com/science/article/pii/S2666693621000256

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