Computer Science ›› 2016, Vol. 43 ›› Issue (10): 272-276.doi: 10.11896/j.issn.1002-137X.2016.10.051

Previous Articles     Next Articles

Research on Structured Method for Chinese Pathological Text

CHEN De-hua, FENG Jie-ying, LE Jia-jin and PAN Piao   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Pathological text as an important kind of unstructured clinical documents,is essential to clinical diagnosis.For the specific Chinese pathological text,this paper put forward a simple and effective structured approach.Firstly the Chinese pathological texts are preprocessed ,including data cleaning,clauses split and trunk extraction,in order to extract the corresponding information of each sample.Then each sample’s final template information is extracted by the way of clauses clustering and statistical parameters filtering.Finally,the templates are used for immediate pathological text structuring process,and the structured results are obtained.Experiments show that the proposed method can achieve satisfactory structured results for similar pathological texts,and the extracted templates will be regularly optimized to meet the needs of the latest text structuring.

Key words: Chinese pathological text,Structuring,Clauses clustering,Template extraction

[1] Chen Jin-xiong.Electronic Medical Record and Electronic Medical Record System[J].Chinese Medical Equipment Journal,2010,31(10):1-7(in Chinese) 陈金雄.电子病历与电子病历系统[J].医疗卫生装备,2010,31(10):1-7
[2] Gunnar E,Bente C,Line S.Developing Large-scale ElectronicPatient Records Conforming to the openEHR Architecture[J].Procedia Technology,2014,16:1281-1286
[3] Hiroshi T,Yasushi M,Takeo O,et al.A Japanese approach to establish an electronic patient record system in an intelligent hospital[J].International Journal of Medical Informatics,1998,49(1):45-51
[4] Hiroshi T,Yasushi M,Shigeki K,et al.Architecture for networked electronic patient record systems[J].International Journal of Medical Informatics,2000,60(2):161-167
[5] Emilia A,Channin D S,Demner-Fushman Dina,et al.Automatic segmentation of clinical texts[C]∥Annual International Conference of the IEEE Engineering in Medicine and Biology Society.Antalya,2009:5905-5908
[6] Maria S,Maria K,Nilsson G H,et al.Automatic recognition of disorders,findings,pharmaceuticals and body structures from clinical text:An annotation and machine learning study[J].Journal of Biomedical Informatics,2014,49(5):148-158
[7] Savova G K,Masanz J J,Ogren P V,et al.Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES):architecture,component evaluation and applications[J].American Medical Informatics Association,2010,17(5):507-513
[8] Carol F,Lyudmila S,Yves L,et al.Automated encoding of clinical documents based on natural language processing[J].American Medical Informatics Association,2004,11(5):392-402
[9] Kong Xiao-feng,Li Ying,Li Hao-min,et al.Structurization ofDigestive Endoscopy Report Based on NLP[J].Chinese Journal of Medical Instrumentation,2008,32(5):348-351(in Chinese) 孔晓风,李莹,李昊旻,等.基于自然语言处理技术的消化科内窥镜检查报告的结构化[J].中国医疗器械杂志,2008,32(5):348-351
[10] 张华平.NLPIR汉语分词系统.http://ictclas.nlpir.org
[11] 邱锡鹏.中文自然语言处理工具包FNLP.https://github.com/xpqiu/fnlp
[12] Steven B,Ewan K,Loper Edward,et al.NLTK.http://www.nltk.org
[13] Mima H,Ananiadou S.An application and evalution of the C/NC-value approach for the automatic term recognition of multi-word units in Japanese[J].International Journal on Terminology,2001,6(2):175-194
[14] Frantzi K T,Ananiandou Sophia.Extracting nested collections[C]∥Proceeding COLING’96 Proeeedings of the 16’,Confe-rence on Association Computational Linguistic.Stroudsburg,1996:41-47
[15] 吴军.数学之美[M].北京:人民邮电出版社,2012
[16] Zhai Dong-hai,Yu Jiang,Gao Fei,et al.K-means text clustering algorithm based on initial cluster centers selection according to maximum distance[J].Application Research of Computers,2014,31(3):713-719(in Chinese) 翟东海,鱼江,高飞,等.最大距离法选取初始簇中心的K-means文本聚类算法的研究[J].计算机应用研究,2014,31(3):713-719
[17] He Hui,Chen Bo,Xu Wei-ran,et al.Short Text Feature Extraction and Clustering for Web Topic Mining[C]∥Third International Conference on Semantics.Knowledge,and Grid,2007:382-385

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!