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本文引用的文献

1
Creation of a new longitudinal corpus of clinical narratives.创建一个新的临床叙事纵向语料库。
J Biomed Inform. 2015 Dec;58 Suppl(Suppl):S6-S10. doi: 10.1016/j.jbi.2015.09.018. Epub 2015 Oct 1.
2
A context-aware approach for progression tracking of medical concepts in electronic medical records.一种用于电子病历中医学概念进展跟踪的上下文感知方法。
J Biomed Inform. 2015 Dec;58 Suppl(Suppl):S150-S157. doi: 10.1016/j.jbi.2015.09.013. Epub 2015 Sep 30.
3
Hidden Markov model using Dirichlet process for de-identification.使用狄利克雷过程进行去识别的隐马尔可夫模型。
J Biomed Inform. 2015 Dec;58 Suppl(Suppl):S60-S66. doi: 10.1016/j.jbi.2015.09.004. Epub 2015 Sep 25.
4
Textual inference for eligibility criteria resolution in clinical trials.用于解决临床试验中纳入标准的文本推理
J Biomed Inform. 2015 Dec;58 Suppl(Suppl):S211-S218. doi: 10.1016/j.jbi.2015.09.008. Epub 2015 Sep 14.
5
Comparison of UMLS terminologies to identify risk of heart disease using clinical notes.使用临床记录比较统一医学语言系统术语以识别心脏病风险
J Biomed Inform. 2015 Dec;58 Suppl(Suppl):S103-S110. doi: 10.1016/j.jbi.2015.08.025. Epub 2015 Sep 12.
6
A hybrid model for automatic identification of risk factors for heart disease.一种用于自动识别心脏病风险因素的混合模型。
J Biomed Inform. 2015 Dec;58 Suppl(Suppl):S171-S182. doi: 10.1016/j.jbi.2015.09.006. Epub 2015 Sep 12.
7
An automatic system to identify heart disease risk factors in clinical texts over time.一个用于长期识别临床文本中心脏病风险因素的自动系统。
J Biomed Inform. 2015 Dec;58 Suppl(Suppl):S158-S163. doi: 10.1016/j.jbi.2015.09.002. Epub 2015 Sep 8.
8
Coronary artery disease risk assessment from unstructured electronic health records using text mining.利用文本挖掘技术从非结构化电子健康记录中进行冠状动脉疾病风险评估。
J Biomed Inform. 2015 Dec;58 Suppl(Suppl):S203-S210. doi: 10.1016/j.jbi.2015.08.003. Epub 2015 Aug 28.
9
Annotating longitudinal clinical narratives for de-identification: The 2014 i2b2/UTHealth corpus.用于去识别化的纵向临床记录标注:2014年i2b2/德克萨斯大学健康科学中心语料库
J Biomed Inform. 2015 Dec;58 Suppl(Suppl):S20-S29. doi: 10.1016/j.jbi.2015.07.020. Epub 2015 Aug 28.
10
Adapting existing natural language processing resources for cardiovascular risk factors identification in clinical notes.调整现有自然语言处理资源以识别临床记录中的心血管危险因素。
J Biomed Inform. 2015 Dec;58 Suppl(Suppl):S128-S132. doi: 10.1016/j.jbi.2015.08.002. Epub 2015 Aug 28.

Practical applications for natural language processing in clinical research: The 2014 i2b2/UTHealth shared tasks.

作者信息

Uzuner Özlem, Stubbs Amber

机构信息

Department of Information Studies, State University of New York at Albany, Albany, NY, USA.

School of Library and Information Science, Simmons College, Boston, MA, USA.

出版信息

J Biomed Inform. 2015 Dec;58 Suppl(Suppl):S1-S5. doi: 10.1016/j.jbi.2015.10.007. Epub 2015 Oct 24.

DOI:10.1016/j.jbi.2015.10.007
PMID:26515500
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4978169/
Abstract
摘要