Using Bayesian networks and importance measures to indentify tumour markers for breast cancer

Shubin Si, Guanmin Liu, Zhiqiang Cai, Peng Xia

科研成果: 书/报告/会议事项章节会议稿件同行评审

4 引用 (Scopus)

摘要

Because breast cancer has become one the most common cancer among women, this paper identified some effective tumour markers from historical patient records to support cancer diagnosis. First, the advantages of Bayesian network (BN) in target classification are discussed, and the concept of importance measures are introduced. Then, the original breast cancer data records used for case study are collected from the first affiliated hospital of medical college of Xi'an Jiaotong University, China, which are also discretized and cleared to form the standard modelling dataset. Finally, the practical BN model of each target variable is learned from the dataset respectively according to the tumour marker variables of breast cancer. Based on the constructed BN models, the importance values of all tumour marker states are calculated and discussed for tumour marker identification.

源语言英语
主期刊名IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2011
1826-1830
页数5
DOI
出版状态已出版 - 2011
活动IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2011 - Singapore, 新加坡
期限: 6 12月 20119 12月 2011

出版系列

姓名IEEE International Conference on Industrial Engineering and Engineering Management
ISSN(印刷版)2157-3611
ISSN(电子版)2157-362X

会议

会议IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2011
国家/地区新加坡
Singapore
时期6/12/119/12/11

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