基于领域语义知识库的疾病辅助诊断方法
CSTR:
作者:
作者单位:

作者简介:

陈德彦(1977-),男,博士,正高级工程师,主要研究领域为自然语言处理,语义Web,知识工程,数据挖掘,机器学习,网络与信息安全.
赵宏(1954-),男,博士,教授,博士生导师,CCF高级会员,主要研究领域为下一代网络,网络与信息安全,网络管理,图像处理.
张霞(1965-),女,博士,教授,博士生导师,CCF高级会员,主要研究领域为软件架构,软件工程,数据库,大数据,人工智能.

通讯作者:

陈德彦,E-mail:deyan_chen@126.com

中图分类号:

基金项目:

国家自然科学基金(61232015);国家高技术研究发展计划(2015AA020103);国家重点研发计划(2016YFC1303000);沈阳东软智能医疗科技研究院有限公司开放课题基金(NRIHTOP1802)


Aided Diagnosis Method for Diseases Based on the Domain Semantic Knowledge Base
Author:
Affiliation:

Fund Project:

National Natural Science Foundation of China (61232015); National High-Tech Research and Development Plan of China (863) (2015AA020103); National Key Research and Development Program of China (2016YFC1303000); Open Program of Neusoft Research of Intelligent Healthcare Technology, Co. Ltd. (NRIHTOP1802)

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    健康医疗领域是一个知识密集型的领域,临床诊断的质量主要依赖于医生所掌握的健康医疗知识以及临床经验.然而,单个医生的能力仍然非常有限,所以目前临床诊断的质量并不高.为此,提出一种基于领域语义知识库的疾病辅助诊断方法,基于Freebase中medicine主题域的知识建立了领域语义知识库,提出计算知识库中症状于疾病诊断的权重、计算与患者输入症状集相关的疾病的相关度和基于患者输入症状集推荐相关症状的算法.最后,基于随机选取的6种常见疾病的临床病历数据对所提出的方法与现有方法进行了对比评价,评价结果一方面表明了所提方法对已有方法存在的问题和不足的改进效果,另一方面也表明所提方法可以避免“冷启动”问题,可以快速支撑对大量常见疾病的辅助诊断.基于所提方法,有望为基层全科医生提供大量常见疾病的辅助诊断服务,或者为患者提供疾病自诊服务.

    Abstract:

    The health care domain is a knowledge-intensive domain. The quality of clinical diagnosis depends mainly on the knowledge of health care and clinical experience held by doctors. However, the ability of a single doctor is very limited, so the quality of clinical diagnosis is not high. To this end, this study proposes an aided diagnosis method based on the domain semantic knowledge base. Firstly, based on the knowledge of the medicine subject matter domain in Freebase, a domain semantic knowledge base is established. Then, based on the semantic knowledge base, the algorithms for calculating the weights of the symptoms in the knowledge base, the relevancy of the diseases related to the input symptom set from a patient, and the related symptom set related to the input symptom set from the patient are proposed. Finally, based on the clinical data of 6 kinds of common diseases randomly selected, the method proposed in this study is compared with the existing methods. On the one hand, the evaluation results show that the method of this paper improves the problems and deficiencies of the existing methods. On the other hand, it shows that the method can avoid the “cold start” problem and can quickly support the aided diagnosis of a large number of common diseases. Using the method presented in this paper, it is expected to provide a comprehensive diagnosis service for a large number of common diseases for the general practitioners at the grassroots level, or provide patients with self-diagnosis services for diseases.

    参考文献
    相似文献
    引证文献
引用本文

陈德彦,赵宏,张霞.基于领域语义知识库的疾病辅助诊断方法.软件学报,2020,31(10):3167-3183

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2018-01-25
  • 最后修改日期:2018-08-12
  • 录用日期:
  • 在线发布日期: 2020-10-12
  • 出版日期: 2020-10-06
文章二维码
您是第位访问者
版权所有:中国科学院软件研究所 京ICP备05046678号-3
地址:北京市海淀区中关村南四街4号,邮政编码:100190
电话:010-62562563 传真:010-62562533 Email:jos@iscas.ac.cn
技术支持:北京勤云科技发展有限公司

京公网安备 11040202500063号