DOI:
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

基金项目:


The diagnostic rules of peripheral lung cancer preliminary study based on data mining technique
Author:
Affiliation:

Fund Project:

  • 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:

    Abstract:

    Objective: To discuss the clinical and imaging diagnostic rules of peripheral lung cancer by data mining technique, and to explore new ideas in the diagnosis of peripheral lung cancer, and to obtain early-stage technology and knowledge support of computer-aided detecting(CAD). Methods: 58 cases of peripheral lung cancer confirmed by clinical pathology were collected. The data were imported into the database after the standardization of the clinical and CT findings attributes were identified. The data was studied comparatively based on Association Rules (AR) of the knowledge discovery process and the Rough Set (RS) reduction algorithm and Genetic Algorithm(GA) of the generic data analysis tool (ROSETTA), respectively. Results: The genetic classification algorithm of ROSETTA generates 5 000 or so diagnosis rules. The RS reduction algorithm of Johnson`s Algorithm generates 51 diagnosis rules and the AR algorithm generates 123 diagnosis rules. Three data mining methods basically consider gender, age, cough, location, lobulation sign, shape, ground-glass density attributes as the main basis for the diagnosis of peripheral lung cancer. Conclusion: These diagnosis rules for peripheral lung cancer with three data mining technology is same as clinical diagnostic rules, and these rules also can be used to build the knowledge base of expert system. This study demonstrated the potential values of data mining technology in clinical imaging diagnosis and differential diagnosis.

    参考文献
    相似文献
    引证文献
引用本文

Yongqian Qiang, Youmin Guo, Xue Li, Qiuping Wang, Hao Chen, Duwu Cui.[J].南京医科大学学报(自然科学版),2007,(3):190-195

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:
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期:
  • 出版日期:
通知关闭
郑重声明