A comparison of natural language processing to ICD-10 codes for identification and characterization of pulmonary embolism.

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Abstract

The 10th revision of the International Classification of Diseases (ICD-10) codes is frequently used to identify pulmonary embolism (PE) events, although the validity of ICD-10 has been questioned. Natural language processing (NLP) is a novel tool that may be useful for pulmonary embolism identification.

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Journal

Journal ID (iso-abbrev): Thromb Res

Title: Thrombosis research

Publisher: Elsevier BV

ISSN (Electronic): 1879-2472

ISSN (Print): 0049-3848

Publication date (Electronic): Jul 2021

Volume: 203

Affiliations

[1 ] Division of General Internal Medicine, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States of America; Thrombosis Service, University of Utah Health, Salt Lake City, UT, United States of America. Electronic address: stacy.a.johnson@hsc.utah.edu.

[2 ] Division of General Internal Medicine, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States of America; Thrombosis Service, University of Utah Health, Salt Lake City, UT, United States of America.

[3 ] Department of Biomedical Informatics, University of Utah School of Medicine, Salt Lake City, UT, United States of America.

[4 ] Division of General Internal Medicine, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States of America.

[5 ] Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, United States of America.

[6 ] University of Utah, College of Pharmacy, Department of Pharmacotherapy, Salt Lake City, UT, United States of America; University of Utah, School of Medicine, Department of Population Health, Salt Lake City, UT, United States of America.

[7 ] Thrombosis Service, University of Utah Health, Salt Lake City, UT, United States of America; University of Utah, College of Pharmacy, Department of Pharmacotherapy, Salt Lake City, UT, United States of America.

Article

Publisher Item ID: S0049-3848(21)00313-3

DOI: 10.1016/j.thromres.2021.04.020

PubMed ID: 34044246

SO-VID: 37fe3399-e0b1-4fb2-9693-5ead074ea9cc

History

Keywords: NLP,Accuracy,Pulmonary embolism,Natural language processing,ICD-10

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Keywords: NLP, Accuracy, Pulmonary embolism, Natural language processing, ICD-10

A comparison of natural language processing to ICD-10 codes for identification and characterization of pulmonary embolism.

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Radiology and Natural Language Processing

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