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龚乐君等:基于领域词典与CF双层标注的中文电子病历实体识别 475· medical named entity recognition.Appl Res Comput,2015,32(4): (杨锦锋,关毅,何彬,等.中文电子病历命名实体和实体关系语 1082 料库构建.软件学报,2016,27(11):2725) (栗伟,赵大哲,李博,等.CRF与规则相结合的医学病历实体识 [24]Uzuner O,South B R,Shen S Y,et al.2010 i2b2/VA challenge on 别.计算机应用研究,2015.32(4):1082) concepts,assertions,and relations in clinical text.JAm Med Inf [21]Shi C Y,Xu Z J,Yang X J.Study of TFIDF algorithm.J Comput Ass0c,2011,18(5):552 4ppl,2009,29(Suppl1上:167 [25]Vaswani A,Shazeer N,Parmar N,et al.Attention is all you (施聪莺,徐朝军,杨晓江T℉IDF算法研究综述.计算机应用, need[J/0L.arXivy preprint.(2017-12-06)[2019-09-041 2009,29(增刊1):167) https://arxiv.org/abs/1706.03762 [22]Li H,Statistical learning methods.Beijing:Tsinghua University [26]Luo L,Yang Z,Yang P.et al.An attention-based BiLSTM-CRF Press,2012 approach to document level chemical named entity recognition. (李航.统计学习方法.北京:清华大学出版社,2012) Bioinformatics,2018,34(8):1381 [23]Yang J F,Guan Y,He B,et al.Corpus construction for named [27]Zhang Y,Wang X W,Hou Z,et al.Clinical named entity entities and entity relations on Chinese electronic medical records recognition from Chinese electronic health records via machine JSom,2016.27(11):2725 learning methods.JMIR Med Inf,2018,6(4):e50medical named entity recognition. Appl Res Comput, 2015, 32(4): 1082 (栗伟, 赵大哲, 李博, 等. CRF与规则相结合的医学病历实体识 别. 计算机应用研究, 2015, 32(4):1082) Shi C Y, Xu Z J, Yang X J. Study of TFIDF algorithm. J Comput Appl, 2009, 29(Suppl 1): 167 (施聪莺, 徐朝军, 杨晓江. TFIDF算法研究综述. 计算机应用, 2009, 29(增刊 1):167) [21] Li  H, Statistical learning methods.  Beijing:  Tsinghua  University Press, 2012 (李航. 统计学习方法. 北京: 清华大学出版社, 2012) [22] Yang  J  F,  Guan  Y,  He  B,  et  al.  Corpus  construction  for  named entities and entity relations on Chinese electronic medical records. J Softw, 2016, 27(11): 2725 [23] (杨锦锋, 关毅, 何彬, 等. 中文电子病历命名实体和实体关系语 料库构建. 软件学报, 2016, 27(11):2725) Uzuner O, South B R, Shen S Y, et al. 2010 i2b2/VA challenge on concepts,  assertions,  and  relations  in  clinical  text. J Am Med Inf Assoc, 2011, 18(5): 552 [24] Vaswani  A,  Shazeer  N,  Parmar  N,  et  al.  Attention  is  all  you need[J/OL]. arXiv preprint.  (2017-12-06)  [2019-09-04]. https://arxiv.org/abs/1706.03762 [25] Luo L, Yang Z, Yang P, et al. An attention-based BiLSTM-CRF approach  to  document  level  chemical  named  entity  recognition. Bioinformatics, 2018, 34(8): 1381 [26] Zhang  Y,  Wang  X  W,  Hou  Z,  et  al.  Clinical  named  entity recognition  from  Chinese  electronic  health  records via machine learning methods. JMIR Med Inf, 2018, 6(4): e50 [27] 龚乐君等: 基于领域词典与 CRF 双层标注的中文电子病历实体识别 · 475 ·
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