Using a Genetic-Fuzzy Algorithm as a Computer Aided Breast Cancer Diagnostic Tool

  • Alharbi, Abir (Mathematics Department, King Saud University) ;
  • Tchier, F (Mathematics Department, King Saud University) ;
  • Rashidi, MM (Department of Mechanical Engineering, Tongji University)
  • Published : 2016.07.01


Computer-aided diagnosis of breast cancer is an important medical approach. In this research paper, we focus on combining two major methodologies, namely fuzzy base systems and the evolutionary genetic algorithms and on applying them to the Saudi Arabian breast cancer diagnosis database, to aid physicians in obtaining an early-computerized diagnosis and hence prevent the development of cancer through identification and removal or treatment of premalignant abnormalities; early detection can also improve survival and decrease mortality by detecting cancer at an early stage when treatment is more effective. Our hybrid algorithm, the genetic-fuzzy algorithm, has produced optimized systems that attain high classification performance, with simple and readily interpreted rules and with a good degree of confidence.


Grant : Research Centre of the Female Scientific and Medical Colleges

Supported by : King Saud University


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