Natural Language Processing to Improve Prediction of Incident Atrial Fibrillation Using Electronic Health Records

Natural Language Processing to Improve Prediction of Incident Atrial Fibrillation Using Electronic Health Records

Background Models predicting atrial fibrillation (AF) risk, such as Cohorts for Heart and Aging Research in Genomic Epidemiology AF (CHARGE‐AF), have not performed as well in electronic health records. Natural language processing (NLP) may improve models by using narrative electronic health record t...

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Bibliographic Details
Main Authors: Jeffrey M. Ashburner, Yuchiao Chang, Xin Wang, Shaan Khurshid, Christopher D. Anderson, Kumar Dahal, Dana Weisenfeld, Tianrun Cai, Katherine P. Liao, Kavishwar B. Wagholikar, Shawn N. Murphy, Steven J. Atlas, Steven A. Lubitz, Daniel E. Singer
Format: Article
Language:English
Published: Wiley 2022-08-01
Series:Journal of the American Heart Association: Cardiovascular and Cerebrovascular Disease
Subjects:
atrial fibrillation
natural language processing
predicted risk
Online Access:https://www.ahajournals.org/doi/10.1161/JAHA.122.026014

Internet

https://www.ahajournals.org/doi/10.1161/JAHA.122.026014

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