利用GATE的XML配置文件实现病历短语抽取的机器学习方法
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摘要
本文利用文本工程通用框架软件的XML配置文件,来指定所学文档使用的特征参数、学习算法,实现文本病历医学短语抽取的机器学习。结果计算机能很方便的在大段病程资料中快速自动获取医生所需的医学短语信息。本学习算法具有较好的实用性,达到了预期要求。
Based on XML configuration files of general architecture for text engineering, we specified characteristics and learning algorithm of the documents, and realized machine learning of text records phrase extraction. The result was that computer could automatically obtain the phrases that doctor required from the long course information quickly. This learning algorithm has good practicability and meets the expected demand.
Based on XML configuration files of general architecture for text engineering, we specified characteristics and learning algorithm of the documents, and realized machine learning of text records phrase extraction. The result was that computer could automatically obtain the phrases that doctor required from the long course information quickly. This learning algorithm has good practicability and meets the expected demand.
引文
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[13]Bisin A,Guaitoli D.Information Extraction and norms of mutual protection[J].J Econ Behav Organ,2015,84(1):154-162.
[14]Wiebe J,Riloff E.Finding mutual benefit between subjectivity analysis and information extraction[J].Affect Comput,2015,2(4):175-191.
[15]Sheikh M,Conlon S.A rule-based system to extract financial information[J].J Comput Inf Syst,2015,52(4):10-19.
[16]马续补,郭菊娥.基于GATE的任务信息抽取研究[J].情报杂志,2010,29(1):155-158.
[2]Uzuner O,Solti I,Cadag E.Extracting medication info-rmation from clinical Text[J].J Am Med Inform Assoc,2010,17(5):514-518.
[3]原欢.基于GATE的货物动态邮件信息抽取方法与应用研究[D].南京:南京航天航空大学,2013.
[4]Ke CM,Huang FJ,Lee SS,et al.Use of data mining surveillance system in real time detection and analysis for healthcareassociated infections[J].BMC Proc,2016,(5):30-34.
[5]Tomaszewski JE,Hipp J,Tangrea M,et al.Madabhushi,machine vision and machine learning in digital pathology[J].Pathobiol Hum Dis,2016,(9):3711-3722.
[6]Taroni F,Biedermann A.Bayesian networks[J].Encycl Forensic Sci,2013,(8):351-356.
[7]Alonso AF,Rojo AJL,Rosado MA.Feature selection using support vector machines and bootstrap methods for ventricular fibrillation detection[J].Expert Syst Appl,2016,39(2):1956-1967.
[8]徐永东,权光日,王亚东.基于HL7的电子病历关键信息抽取技术研究[J].哈尔滨工业大学学报,2011,(11):89-94.
[9]叶枫,陈莺莺,周根贵,等.电子病历中命名实体的智能识别[J].中国生物医学工程学报,2011,(2):256-262..
[10]Bouvry C,Tvardik N,Kergourlay I,et al.The SYNODOS project:System for the normalization and organization of textual medical data for observation in healthcare[J].IRBM,2016,37(4):109-115.
[11]Hong JL,Siew EG,Egerton S.Information extraction for search engines using fast heuristic techniques[J].Data Knowl Eng,2010,69(2):169-196.
[12]Cunningham H,Maynard D,Bontcheva K.Developing language processing components with GATE Version 8[EB/OL].http://gateacuk/sale/tao/tao.pdf.
[13]Bisin A,Guaitoli D.Information Extraction and norms of mutual protection[J].J Econ Behav Organ,2015,84(1):154-162.
[14]Wiebe J,Riloff E.Finding mutual benefit between subjectivity analysis and information extraction[J].Affect Comput,2015,2(4):175-191.
[15]Sheikh M,Conlon S.A rule-based system to extract financial information[J].J Comput Inf Syst,2015,52(4):10-19.
[16]马续补,郭菊娥.基于GATE的任务信息抽取研究[J].情报杂志,2010,29(1):155-158.