A modular framework for biomedical concept recognition.
A modular framework for biomedical concept recognition.
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DOI：
10.1186/1471-2105-14-281
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发表时间：
2013-09-24
影响因子：
3
通讯作者：
Oliveira JL
中科院分区：
文献类型：
--
作者：
Campos D;Matos S;Oliveira JL
概念识别是生物医学信息提取中的一项重要任务，提出了一些复杂且尚未解决的挑战。此类解决方案的开发通常以临时方式或使用通用信息提取框架进行，这些框架并未针对生物医学领域进行优化，并且通常需要集成复杂的外部库和/或开发自定义工具。本文介绍 Neji，这是一个针对生物医学概念识别进行优化的开源框架，围绕四个关键特征构建：模块化、可扩展性、速度和可用性。它集成了生物医学自然语言处理模块，例如句子分割、标记化、词形还原、词性标记、分块和依存分析。概念识别是通过字典匹配和具有归一化方法的机器学习来提供的。 Neji 还集成了创新的概念树实现，支持重叠的概念名称和相应的消歧技术。还支持最流行的输入和输出格式，即 Pubmed XML、IeXML、CoNLL 和 A1。除了内置功能之外，开发人员和研究人员还可以实现新的处理模块或管道，或使用提供的命令行界面工具构建自己的解决方案，应用最合适的技术来识别异构生物医学概念。 Neji 针对具有异构生物医学概念的三个黄金标准语料库（CRAFT、AnEM 和 NCBI 疾病语料库）进行了评估，在命名实体识别（重叠匹配的 F1 测量：物种 95%、细胞 92%、细胞成分 83%、基因和蛋白质 76%、化学品 65%、生物过程和分子功能 63%、疾病 85% 和解剖实体 82%）和实体标准化方面取得了高性能结果（F1-测量重叠名称匹配和正确标识符包含在返回的标识符列表中：物种 88%、细胞 71%、细胞成分 72%、基因和蛋白质 64%、化学品 53%、生物过程和分子功能 40%）。 Neji 提供快速、多线程的数据处理，在使用基于词典的概念识别时，注释速度高达 1200 个句子/秒。考虑到所提供的功能和基本特征，我们认为 Neji 对生物医学界做出了重要贡献，简化了复杂概念识别解决方案的开发。 Neji 可在 http://bioinformatics.ua.pt/neji 上免费获取。
Concept recognition is an essential task in biomedical information extraction, presenting several complex and unsolved challenges. The development of such solutions is typically performed in an ad-hoc manner or using general information extraction frameworks, which are not optimized for the biomedical domain and normally require the integration of complex external libraries and/or the development of custom tools. This article presents Neji, an open source framework optimized for biomedical concept recognition built around four key characteristics: modularity, scalability, speed, and usability. It integrates modules for biomedical natural language processing, such as sentence splitting, tokenization, lemmatization, part-of-speech tagging, chunking and dependency parsing. Concept recognition is provided through dictionary matching and machine learning with normalization methods. Neji also integrates an innovative concept tree implementation, supporting overlapped concept names and respective disambiguation techniques. The most popular input and output formats, namely Pubmed XML, IeXML, CoNLL and A1, are also supported. On top of the built-in functionalities, developers and researchers can implement new processing modules or pipelines, or use the provided command-line interface tool to build their own solutions, applying the most appropriate techniques to identify heterogeneous biomedical concepts. Neji was evaluated against three gold standard corpora with heterogeneous biomedical concepts (CRAFT, AnEM and NCBI disease corpus), achieving high performance results on named entity recognition (F1-measure for overlap matching: species 95%, cell 92%, cellular components 83%, gene and proteins 76%, chemicals 65%, biological processes and molecular functions 63%, disorders 85%, and anatomical entities 82%) and on entity normalization (F1-measure for overlap name matching and correct identifier included in the returned list of identifiers: species 88%, cell 71%, cellular components 72%, gene and proteins 64%, chemicals 53%, and biological processes and molecular functions 40%). Neji provides fast and multi-threaded data processing, annotating up to 1200 sentences/second when using dictionary-based concept identification. Considering the provided features and underlying characteristics, we believe that Neji is an important contribution to the biomedical community, streamlining the development of complex concept recognition solutions. Neji is freely available at http://bioinformatics.ua.pt/neji.
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影响因子：
3
作者：
Bada M;Eckert M;Evans D;Garcia K;Shipley K;Sitnikov D;Baumgartner WA Jr;Cohen KB;Verspoor K;Blake JA;Hunter LE
通讯作者：
Hunter LE
DOI：
10.1093/bioinformatics/btn117
发表时间：
2008-06-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Kim JJ;Pezik P;Rebholz-Schuhmann D
通讯作者：
Rebholz-Schuhmann D
DOI：
10.1016/j.ijmedinf.2007.07.004
发表时间：
2008-05-01
影响因子：
4.9
作者：
Jelier, Rob;Schuemie, Martijn J.;Kors, Jan A.
通讯作者：
Kors, Jan A.
影响因子：
7.5
作者：
Bunescu, R;Ge, RF;Wong, YW
通讯作者：
Wong, YW
影响因子：
3
作者：
Campos D;Matos S;Oliveira JL
通讯作者：
Oliveira JL