Mathematical model development to detect breast cancer using multigene genetic programming

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@InProceedings{Hasan:2016:ICIEV,
  author =       "Md. Kamrul Hasan and Md. Milon Islam and 
                 M. M. A. Hashem",
  booktitle =    "2016 5th International Conference on Informatics,
                 Electronics and Vision (ICIEV)",
  title =        "Mathematical model development to detect breast cancer
                 using multigene genetic programming",
  year =         "2016",
  pages =        "574--579",
  abstract =     "Breast cancer is one of the world's leading causes of
                 cancer death of women. Generally, human breast tissue
                 cells emerge this cancer. This causes loss of breast as
                 well as precious lives. Usually in people over 50 years
                 have the risk of this types of cancer. So, early
                 detection for this disease is very crucial to save the
                 valuable lives. This paper develops a 10 fold cross
                 validated mathematical model to detect breast cancer
                 using symbolic regression of multi-gene genetic
                 programming (MGGP). Data for MGGP is retrieved from UCI
                 machine learning repository data set and is used for
                 training and testing the 10 fold cross validated
                 mathematical model. The developed model produces fast
                 and accurate results for both training and testing data
                 set. The error rate is very negligible for both benign
                 and malignant type of breast cancer. The cross
                 validated model shows the higher accuracy with respect
                 to existing techniques.",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/ICIEV.2016.7760068",
  month =        may,
  notes =        "Also known as \cite{7760068}",
}

Genetic Programming entries for Md Kamrul Hasan Md Milon Islam M M A Hashem

Citations