CLAMP - a toolkit for efficiently building customized clinical natural language processing pipelines.

CLAMP - a toolkit for efficiently building customized clinical natural language processing pipelines.
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DOI:
10.1093/jamia/ocx132
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发表时间:
2018-03-01
期刊:
Journal of the American Medical Informatics Association : JAMIA
影响因子:
--
通讯作者:
Xu H
Xu H
中科院分区:
其他
文献类型:
--
作者:
Soysal E;Wang J;Jiang M;Wu Y;Pakhomov S;Liu H;Xu H

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现有的通用临床自然语言处理系统,如MetaMap和临床文本分析与知识提取系统,已经成功地应用于临床文本的信息提取。然而,最终用户通常必须为他们的个人任务定制现有系统,这可能需要大量的NLP技能。在这里,我们介绍了CLAMP(临床语言注释、建模和处理),这是一个新开发的临床NLP工具包,它不仅提供了最先进的NLP组件,而且还提供了一个用户友好的图形用户界面,可以帮助用户快速为他们的个人应用程序构建定制的NLP管道。我们的测试表明,CLAMP缺省流水线在命名实体识别和概念编码方面取得了良好的性能。我们还通过2个用例演示了夹具图形用户界面在构建定制的高性能NLP管道、提取吸烟状态和实验室测试值方面的效率。CLAMP可公开用于研究用途,我们相信它是临床NLP社区的独特资产。
Existing general clinical natural language processing (NLP) systems such as MetaMap and Clinical Text Analysis and Knowledge Extraction System have been successfully applied to information extraction from clinical text. However, end users often have to customize existing systems for their individual tasks, which can require substantial NLP skills. Here we present CLAMP (Clinical Language Annotation, Modeling, and Processing), a newly developed clinical NLP toolkit that provides not only state-of-the-art NLP components, but also a user-friendly graphic user interface that can help users quickly build customized NLP pipelines for their individual applications. Our evaluation shows that the CLAMP default pipeline achieved good performance on named entity recognition and concept encoding. We also demonstrate the efficiency of the CLAMP graphic user interface in building customized, high-performance NLP pipelines with 2 use cases, extracting smoking status and lab test values. CLAMP is publicly available for research use, and we believe it is a unique asset for the clinical NLP community.
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