A deep database of medical abbreviations and acronyms for natural language processing.
A deep database of medical abbreviations and acronyms for natural language processing.
复制标题
自然语言处理的医学缩写和首字母缩写的深度数据库。
DOI：
10.1038/s41597-021-00929-4
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发表时间：
2021-06-02
期刊：
影响因子：
9.8
通讯作者：
Vawdrey DK
中科院分区：
文献类型：
--
作者：
Grossman Liu L;Grossman RH;Mitchell EG;Weng C;Natarajan K;Hripcsak G;Vawdrey DK
医学缩写词和首字母缩略词的识别、消歧和扩展对于防止自然语言处理中出现医学危险的误解至关重要。为了支持识别、消歧和扩展，我们推出了医学缩写和首字母缩略词元库存，这是一个医学缩写的深度数据库。对多个医疗保健专业和环境的八个来源清单进行系统协调，确定了 104,057 个缩写和 170,426 个相应的含义。使用最先进的机器学习对同义记录进行自动交叉映射，减少了冗余，从而简化了未来的应用。其他功能包括半自动质量控制以消除错误。元库存展示了新临床文本中缩写和含义的高度完整性或覆盖率，比第二大存储库有实质性改进（缩写覆盖率增加 6-14%；含义覆盖率增加 28-52%）。据我们所知，元清单是迄今为止最完整的美式英语医学缩写和首字母缩略词汇编。多种来源和高覆盖率支持在不同专业和环境中的应用。这允许跨机构的自然语言处理，这是以前的清单不支持的。元清单可在 https://bit.ly/github-clinical-abbreviations 上获取。描述报告数据的机器可访问元数据文件：10.6084/m9.figshare.14068949
The recognition, disambiguation, and expansion of medical abbreviations and acronyms is of upmost importance to prevent medically-dangerous misinterpretation in natural language processing. To support recognition, disambiguation, and expansion, we present the Medical Abbreviation and Acronym Meta-Inventory, a deep database of medical abbreviations. A systematic harmonization of eight source inventories across multiple healthcare specialties and settings identified 104,057 abbreviations with 170,426 corresponding senses. Automated cross-mapping of synonymous records using state-of-the-art machine learning reduced redundancy, which simplifies future application. Additional features include semi-automated quality control to remove errors. The Meta-Inventory demonstrated high completeness or coverage of abbreviations and senses in new clinical text, a substantial improvement over the next largest repository (6–14% increase in abbreviation coverage; 28–52% increase in sense coverage). To our knowledge, the Meta-Inventory is the most complete compilation of medical abbreviations and acronyms in American English to-date. The multiple sources and high coverage support application in varied specialties and settings. This allows for cross-institutional natural language processing, which previous inventories did not support. The Meta-Inventory is available at https://bit.ly/github-clinical-abbreviations. Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.14068949
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影响因子：
5.1
作者：
Awan, Safia;Abid, Shahab;Hamid, Saeed
通讯作者：
Hamid, Saeed
影响因子：
3
作者：
Jimeno-Yepes AJ;McInnes BT;Aronson AR
通讯作者：
Aronson AR
影响因子：
9.8
作者：
Johnson AE;Pollard TJ;Shen L;Lehman LW;Feng M;Ghassemi M;Moody B;Szolovits P;Celi LA;Mark RG
通讯作者：
Mark RG
影响因子：
11.4
作者：
Chemali, Mark;Hibbert, Emily J.;Sheen, Adrian
通讯作者：
Sheen, Adrian
DOI：
10.1093/jamia/ocaa056
发表时间：
2020-05-29
期刊：
Journal of the American Medical Informatics Association : JAMIA
影响因子：
--
作者：
Lu CJ;Payne A;Mork JG
通讯作者：
Mork JG