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Using UMLS to construct a generalized hierarchical concept-based dictionary of brain functions for information extraction from the fMRI literature.

机译:使用UMLS来构建基于广义层次概念的脑功能字典,以便从fMRI文献中提取信息。

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With a rapid progress in the field, a great many fMRI studies are published every year, to the extent that it is now becoming difficult for researchers to keep up with the literature, since reading papers is extremely time-consuming and labor-intensive. Thus, automatic information extraction has become an important issue. In this study, we used the Unified Medical Language System (UMLS) to construct a hierarchical concept-based dictionary of brain functions. To the best of our knowledge, this is the first generalized dictionary of this kind. We also developed an information extraction system for recognizing, mapping and classifying terms relevant to human brain study. The precision and recall of our system was on a par with that of human experts in term recognition, term mapping and term classification. Our approach presented in this paper presents an alternative to the more laborious, manual entry approach to information extraction.
机译:随着该领域的快速发展,每年都会发表大量的fMRI研究,以至于研究人员现在很难跟上文献的速度,因为阅读论文非常耗时且劳动强度大。因此,自动信息提取已经成为重要的问题。在这项研究中,我们使用统一医学语言系统(UMLS)构建基于层次概念的脑功能字典。据我们所知,这是第一本此类通用词典。我们还开发了一种信息提取系统,用于识别,映射和分类与人脑研究相关的术语。我们的系统的精确度和召回率与术语识别,术语映射和术语分类方面的人类专家相当。本文介绍的方法为信息提取中较费力的手动输入方法提供了一种替代方法。

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