Biomedical term mapping databases.
Biomedical term mapping databases.
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DOI：
10.1093/nar/gki137
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发表时间：
2005-01-01
影响因子：
14.9
通讯作者：
Altman RB
中科院分区：
文献类型：
--
作者：
Wren JD;Chang JT;Pustejovsky J;Adar E;Garner HR;Altman RB
为了提高交流效率，较长的单词和短语经常被映射到较短的形式，如缩写或首字母缩写。这些缩略语普遍存在于生物学和医学的各个方面，随着生物医学文献数量的增长，缩略语的数量和每个缩略语的平均定义数量也在增加。更令人困惑的是，不同的作者通常会以不同的方式缩写相同的单词/短语。这种模糊性阻碍了我们检索信息、整合数据库和挖掘文本数据库内容的能力。对命名法进行标准化的努力，特别是那些追溯命名法的努力，需要意识到不同的缩写映射和拼写变化。为了解决这个问题，已经有了几项努力来开发计算机算法，以在大量文献中识别短词和长词之间的映射。到目前为止，已经应用了四种这样的算法来创建在MEDLINE内全面映射生物医学术语和缩写的在线数据库：ARGH(http://lethargy.swmed.edu/ARGH/argh.asp)，，斯坦福生物医学缩写服务器(http://bionlp.stanford.edu/abbreviation/)，AcroMed(http://medstract.med.tufts.edu/acro1.1/index.htm)和SARAD(http://www.hpl.hp.com/research/idl/projects/abbrev.html).除了作为有用的计算工具外，这些数据库还充当有价值的参考资料，帮助生物学家跟上不断扩大的术语词汇表。
Longer words and phrases are frequently mapped onto a shorter form such as abbreviations or acronyms for efficiency of communication. These abbreviations are pervasive in all aspects of biology and medicine and as the amount of biomedical literature grows, so does the number of abbreviations and the average number of definitions per abbreviation. Even more confusing, different authors will often abbreviate the same word/phrase differently. This ambiguity impedes our ability to retrieve information, integrate databases and mine textual databases for content. Efforts to standardize nomenclature, especially those doing so retrospectively, need to be aware of different abbreviatory mappings and spelling variations. To address this problem, there have been several efforts to develop computer algorithms to identify the mapping of terms between short and long form within a large body of literature. To date, four such algorithms have been applied to create online databases that comprehensively map biomedical terms and abbreviations within MEDLINE: ARGH (http://lethargy.swmed.edu/ARGH/argh.asp), the Stanford Biomedical Abbreviation Server (http://bionlp.stanford.edu/abbreviation/), AcroMed (http://medstract.med.tufts.edu/acro1.1/index.htm) and SaRAD (http://www.hpl.hp.com/research/idl/projects/abbrev.html). In addition to serving as useful computational tools, these databases serve as valuable references that help biologists keep up with an ever-expanding vocabulary of terms.
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