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Review
. 2020 Sep:109:103526.
doi: 10.1016/j.jbi.2020.103526. Epub 2020 Aug 6.

Clinical concept extraction: A methodology review

Sunyang Fu  1 , David Chen  2 , Huan He  3 , Sijia Liu  4 , Sungrim Moon  5 , Kevin J Peterson  6 , Feichen Shen  7 , Liwei Wang  8 , Yanshan Wang  9 , Andrew Wen  10 , Yiqing Zhao  11 , Sunghwan Sohn  12 , Hongfang Liu  13
Affiliations
Review

Clinical concept extraction: A methodology review

Sunyang Fu et al. J Biomed Inform. 2020 Sep.

Abstract

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.

Keywords: Concept extraction; Deep learning; Electronic health records; Information extraction; Machine learning; Natural language processing.

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Conflict of interest statement

Competing Interests

The authors have no competing interests to declare.

Figures

Figure 1.
Figure 1.
An example of using concept extraction for stroke research.
Figure 2.
Figure 2.
Overview of article selection process.
Figure 3.
Figure 3.
Trend view of clinical concept extraction research over different approaches.
Figure 4.
Figure 4.
Overview of the method utilization.
Figure 5.
Figure 5.
The development process of clinical concept extraction applications.
Figure 6.
Figure 6.
Data collection and corpus annotation process.
See this image and copyright information in PMC

References

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    1. Wang Y, Wang L, Rastegar-Mojarad M, Moon S, Shen F, Afzal N, et al. Clinical information extraction applications: A literature review. Journal of Biomedical Informatics. 2018;77:34–49. - PMC - PubMed

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