BENTO: A Visual Platform for Building Clinical NLP Pipelines Based on CodaLab.
BENTO: A Visual Platform for Building Clinical NLP Pipelines Based on CodaLab.
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Bento：一个基于Codalab的临床NLP管道的视觉平台。
DOI：
10.18653/v1/2020.acl-demos.13
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发表时间：
2020-07
期刊：
影响因子：
--
通讯作者：
Yu H
中科院分区：
文献类型：
--
作者：
Jin Y;Li F;Yu H
CodaLab1 is an open-source web-based platform for collaborative computational research. Although CodaLab has gained popularity in the research community, its interface has limited support for creating reusable tools that can be easily applied to new datasets and composed into pipelines. In clinical domain, natural language processing (NLP) on medical notes generally involves multiple steps, like tokenization, named entity recognition, etc. Since these steps require different tools which are usually scattered in different publications, it is not easy for researchers to use them to process their own datasets. In this paper, we present BENTO, a workflow management platform with a graphic user interface (GUI) that is built on top of CodaLab, to facilitate the process of building clinical NLP pipelines. BENTO comes with a number of clinical NLP tools that have been pre-trained using medical notes and expert annotations and can be readily used for various clinical NLP tasks. It also allows researchers and developers to create their custom tools (e.g., pre-trained NLP models) and use them in a controlled and reproducible way. In addition, the GUI interface enables researchers with limited computer background to compose tools into NLP pipelines and then apply the pipelines on their own datasets in a “what you see is what you get” (WYSIWYG) way. Although BENTO is designed for clinical NLP applications, the underlying architecture is flexible to be tailored to any other domains.
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影响因子：
3.2
作者：
Jin, Yonghao;Li, Fei;Yu, Hong
通讯作者：
Yu, Hong
影响因子：
7.5
作者：
He, Bin;Guan, Yi;Dai, Rui
通讯作者：
Dai, Rui
通过循环神经网络和条件随机场对临床记录进行去识别
影响因子：
4.5
作者：
Liu Z;Tang B;Wang X;Chen Q
通讯作者：
Chen Q
影响因子：
7.4
作者：
Lalor, John P.;Woolf, Beverly;Yu, Hong
通讯作者：
Yu, Hong
影响因子：
3.2
作者：
Li, Fei;Jin, Yonghao;Yu, Hong
通讯作者：
Yu, Hong