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  • 标题:GA-based Feature Selection with ANFIS Approach to Breast Cancer Recurrence
  • 本地全文:下载
  • 作者:Hamza Turabieh
  • 期刊名称:International Journal of Computer Science Issues
  • 印刷版ISSN:1694-0784
  • 电子版ISSN:1694-0814
  • 出版年度:2016
  • 卷号:13
  • 期号:1
  • 出版社:IJCSI Press
  • 摘要:Automatic disease diagnosis systems are important for medical fields. These systems have been used to help doctors to make better diagnosis. Breast cancer is a very common class of cancers among women. In this paper, we focus on breast cancer recurrence problem, hybridizing two methodologies, Genetic Algorithm (GA) and Adaptive Neuro Fuzzy Inference System (ANFIS), to develop a good diagnosis system. GA has been used as a selection algorithm to find the best features, whilst ANFIS has been used as a classifier algorithm. The robustness of the proposed hybrid methodology is examined using classification accuracy, sensitivity, and specificity. The proposed hybrid algorithm has achieved accuracy of 88% for training dataset and 71% for testing. The results demonstrate the effective interpretation and point out the ability to design a good diagnosis system
  • 关键词:Breast cancer; Feature Selection; Genetic Algorithm; ANFIS
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