This paper is in the following e-collection/theme issue:

Natural Language Processing (636)

Published on in Vol 7, No 3 (2019): Jul-Sep

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/13331, first published .
Improving the Efficacy of the Data Entry Process for Clinical Research With a Natural Language Processing–Driven Medical Information Extraction System: Quantitative Field Research

Improving the Efficacy of the Data Entry Process for Clinical Research With a Natural Language Processing–Driven Medical Information Extraction System: Quantitative Field Research

Improving the Efficacy of the Data Entry Process for Clinical Research With a Natural Language Processing–Driven Medical Information Extraction System: Quantitative Field Research

Authors of this article:

Jiang Han1, 2 Author Orcid Image ;   Ken Chen3 Author Orcid Image ;   Lei Fang3 Author Orcid Image ;   Shaodian Zhang3, 4 Author Orcid Image ;   Fei Wang3, 5 Author Orcid Image ;   Handong Ma3, 6 Author Orcid Image ;   Liebin Zhao2, 7 Author Orcid Image ;   Shijian Liu1, 2 Author Orcid Image
Article Authors Cited by (12) Tweetations (4) Metrics

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  2. Wang J, Deng H, Liu B, Hu A, Liang J, Fan L, Zheng X, Wang T, Lei J. Systematic Evaluation of Research Progress on Natural Language Processing in Medicine Over the Past 20 Years: Bibliometric Study on PubMed. Journal of Medical Internet Research 2020;22(1):e16816 View
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