Large-scale biomedical concept recognition: an evaluation of current automatic annotators and their parameters.
Large-scale biomedical concept recognition: an evaluation of current automatic annotators and their parameters.
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DOI：
10.1186/1471-2105-15-59
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发表时间：
2014-02-26
影响因子：
3
通讯作者：
Verspoor K
中科院分区：
文献类型：
--
作者：
Funk C;Baumgartner W Jr;Garcia B;Roeder C;Bada M;Cohen KB;Hunter LE;Verspoor K
本体概念对于许多不同的生物医学任务是有用的。概念很难在文本中识别，这是由于本体中捕获的内容与概念在文本中的表达方式之间存在脱节。有许多识别特定的本体，但一个通用的方法，概念识别是一个开放的问题。三个基于词典的系统（MetaMap，NCBO注释器，和ConceptMapper）的评估在科罗拉多丰富的注释全文（CRAFT）语料库的八个生物医学本体。超过1,000个参数组合进行了检查，并为每个系统本体对性能最佳的参数。建立了三个系统对八个生物医学本体的概念识别基线（F-测量范围从0.14-0.83）。在我们测试的三个系统中，ConceptMapper通常是性能最好的系统;它在八个本体中产生了七个最高的F测量。默认参数对于大多数本体上的大多数系统来说并不理想;通过改变参数，F-measure可以增加到0.4。不仅是最好的性能参数，但建议选择最佳参数的基础上本体的特点。
Ontological concepts are useful for many different biomedical tasks. Concepts are difficult to recognize in text due to a disconnect between what is captured in an ontology and how the concepts are expressed in text. There are many recognizers for specific ontologies, but a general approach for concept recognition is an open problem. Three dictionary-based systems (MetaMap, NCBO Annotator, and ConceptMapper) are evaluated on eight biomedical ontologies in the Colorado Richly Annotated Full-Text (CRAFT) Corpus. Over 1,000 parameter combinations are examined, and best-performing parameters for each system-ontology pair are presented. Baselines for concept recognition by three systems on eight biomedical ontologies are established (F-measures range from 0.14–0.83). Out of the three systems we tested, ConceptMapper is generally the best-performing system; it produces the highest F-measure of seven out of eight ontologies. Default parameters are not ideal for most systems on most ontologies; by changing parameters F-measure can be increased by up to 0.4. Not only are best performing parameters presented, but suggestions for choosing the best parameters based on ontology characteristics are presented.
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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
影响因子：
3
作者：
Jimeno A;Jimenez-Ruiz E;Lee V;Gaudan S;Berlanga R;Rebholz-Schuhmann D
通讯作者：
Rebholz-Schuhmann D
DOI：
10.1016/b978-012373583-6.50018-9
发表时间：
2008-01-01
期刊：
BIOMEDICAL INFORMATION TECHNOLOGY
影响因子：
--
作者：
Chu, Wesley W.;Liu, Zhenyu;Zou, Qinghua
通讯作者：
Zou, Qinghua
影响因子：
5.8
作者：
DeLuca, David S.;Beisswanger, Elena;Blasczyk, Rainer
通讯作者：
Blasczyk, Rainer
使用证据内容在文本中找到基因组本体术语。
影响因子：
3
作者：
Couto, FM;Silva, MJ;Coutinho, PM
通讯作者：
Coutinho, PM