Clinical concept extraction: A methodology review

被引：92

作者：

Fu, Sunyang ^{[1
,3
]}

Chen, David ^{[1
]}

He, Huan ^{[1
]}

Liu, Sijia ^{[1
]}

Moon, Sungrim ^{[1
]}

Peterson, Kevin J. ^{[2
,3
]}

Shen, Feichen ^{[1
]}

Wang, Liwei ^{[1
]}

Wang, Yanshan ^{[1
]}

Wen, Andrew ^{[1
]}

Zhao, Yiqing ^{[1
]}

Sohn, Sunghwan ^{[1
]}

Liu, Hongfang ^{[1
,3
]}

机构：

[1] Mayo Clin, Dept Hlth Sci Res, 200 First St SW, Rochester, MN 55905 USA

[2] Mayo Clin, Dept Informat Technol, 200 First St SW, Rochester, MN 55905 USA

[3] Univ Minnesota Twin Cities, Minneapolis, MN 55455 USA

来源：

JOURNAL OF BIOMEDICAL INFORMATICS | 2020年 / 109卷

关键词：

Concept extraction; Natural language processing; Information extraction; Electronic health records; Machine learning; Deep learning; NAMED ENTITY RECOGNITION; OF-THE-ART; PROTECTED HEALTH INFORMATION; CONVOLUTIONAL NEURAL-NETWORK; MEDICATION INFORMATION; DE-IDENTIFICATION; RISK-FACTORS; MULTIPLE-SCLEROSIS; RADIOLOGY REPORTS; ADVERSE EVENTS;

D O I：

10.1016/j.jbi.2020.103526

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Background: Concept extraction, a subdomain of natural language processing (NLP) with a focus on extracting concepts of interest, has been adopted to computationally extract clinical information from text for a wide range of applications ranging from clinical decision support to care quality improvement. Objectives: In this literature review, we provide a methodology review of clinical concept extraction, aiming to catalog development processes, available methods and tools, and specific considerations when developing clinical concept extraction applications. Methods: Based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a literature search was conducted for retrieving EHR-based information extraction articles written in English and published from January 2009 through June 2019 from Ovid MEDLINE In-Process & Other Non-Indexed Citations, Ovid MEDLINE, Ovid EMBASE, Scopus, Web of Science, and the ACM Digital Library. Results: A total of 6,686 publications were retrieved. After title and abstract screening, 228 publications were selected. The methods used for developing clinical concept extraction applications were discussed in this review.

引用

页数：16

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