面向误诊提示的疾病-症状语义网构建

doi:10.13229/j.cnki.jdxbgxb20170406

吉林大学学报(工学版) ›› 2018, Vol. 48 ›› Issue (3): 859-865.doi: 10.13229/j.cnki.jdxbgxb20170406

面向误诊提示的疾病-症状语义网构建

黄岚^1,2, 纪林影³, 姚刚⁴, 翟睿峰⁵, 白天^1,2

1.吉林大学计算机科学与技术学院,长春 130012;
2.吉林大学符号计算与知识工程教育部重点实验室,长春 130012;
3.吉林大学软件学院,长春 130012;
4.吉林大学第二医院神经内科,长春 130041;
5.长春理工大学电子信息工程学院,长春 130022;

收稿日期:2017-04-21 出版日期:2018-05-20 发布日期:2018-05-20
通讯作者: 白天(1983-),男,副教授,博士.研究方向:生物信息学.E-mail:baitian@jlu.edu.cn
作者简介:黄岚(1974-),女,教授,博士生导师.研究方向:社区发现,数据挖掘,商务智能.E-mail:huanglan@jlu.edu.cn
基金资助:
国家自然科学基金项目(61472159,61702214,61572227); 吉林省重点科技攻关项目(20160204022GX, 20170101006JC, 20170203002GX,20150520064JH); 吉林省产业创新专项项目(2017C030-1,2017C033); 中国博士后科学基金面上项目(2014M561293); 珠海市优势学科项目; 广东省优势重点学科建设项目.

Construction of disease-symptom semantic net for misdiagnosis prompt

HUANG Lan^1,2, JI Lin-ying³, YAO Gang⁴, ZHAI Rui-feng⁵, BAI Tian^1,2

1.College of Computer Science and Technology,Jilin University,Changchun 130012,China;
2.Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education,Jilin University,Changchun 130012,China;
3.College of Software,Jilin University,Changchun 130012,China;
4.Neurological Department,The Second Hospital of Jilin University,Changchun 130041,China;
5.College of Electronical and Information Engineering,Changchun University of Science and Technology,Changchun 130022,China

Received:2017-04-21 Online:2018-05-20 Published:2018-05-20

摘要/Abstract

摘要： 首先,从医疗语料库中识别症状描述词语,基于症状间语义关系构建症状本体。然后,通过文本挖掘抽取疾病与症状间的关系、疾病与疾病间的易误诊关系,建立疾病-症状语义网DSSN。DSSN中包含了疾病本体DO、新构建的症状本体、疾病间的易误诊关系及鉴别诊断知识。最后,通过一个临床诊断中的用例来说明DSSN在临床辅助诊断系统中对易误诊提示的帮助。

关键词: 人工智能, 语义网, 文本挖掘, 误诊, 本体

Abstract: A Disease-Symptom Semantic Net (DSSN) for misdiagnosis prompt is constructed. First, symptom words are recognized from medical corpus, and a symptom ontology based on semantic relations between symptom words is established. Then, the relations between diseases and symptoms and the misdiagnosed relations between diseases were test mined and extracted to construct DSSN. DSSN contains Disease Ontology (DO), new established symptom ontology, misdiagnosed relations between diseases and differential diagnosis knowledge. Finally, a use case in clinical diagnosis is used to illustrate that DSSN is helpful to prompt misdiagnosis in clinical assistance diagnosis system.

Key words: artificial intelligence, semantic network, text mining, misdiagnosis, ontology

中图分类号:

TP182

黄岚, 纪林影, 姚刚, 翟睿峰, 白天. 面向误诊提示的疾病-症状语义网构建[J]. 吉林大学学报(工学版), 2018, 48(3): 859-865.

HUANG Lan, JI Lin-ying, YAO Gang, ZHAI Rui-feng, BAI Tian. Construction of disease-symptom semantic net for misdiagnosis prompt[J]. 吉林大学学报(工学版), 2018, 48(3): 859-865.

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面向误诊提示的疾病-症状语义网构建

Construction of disease-symptom semantic net for misdiagnosis prompt

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