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",
• month = may,
• keywords = "genetic algorithms, genetic programming, Breast cancer, multigene genetic programming, cross validation, confusion matrix, symbolic regression, mathematical model",
• DOI = "doi:10.1109/ICIEV.2016.7760068",
• size = "6 pages",
• 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.",
• notes = "Also known as \cite{7760068}",

}

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

Citations