Developing a Mathematical Model to Detect Diabetes Using Multigene Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@Article{oai:thesai.org:10.14569/IJARAI.2014.031007,

• author = "Ahlam A Sharief and Alaa Sheta",
• title = "Developing a Mathematical Model to Detect Diabetes Using Multigene Genetic Programming",
• journal = "International Journal of Advanced Research in Artificial Intelligence (IJARAI)",
• publisher = "The Science and Information (SAI) Organization",
• year = "2014",
• number = "10",
• volume = "3",
• keywords = "genetic algorithms, genetic programming, diabetes, classification, pima indian data",
• bibsource = "OAI-PMH server at thesai.org",
• language = "eng",
• oai = "oai:thesai.org:10.14569/IJARAI.2014.031007",
• URL = "http://thesai.org/Downloads/IJARAI/Volume3No10/Paper_7-Developing_a_Mathematical_Model_to_Detect.pdf",
• DOI = "doi:10.14569/IJARAI.2014.031007",
• size = "6 pages",
• abstract = "Diabetes Mellitus is one of the deadly diseases growing at a rapid rate in the developing countries. Diabetes Mellitus is being one of the major contributors to the mortality rate. It is the sixth reason for death worldwide. Early detection of the disease is highly recommended. This paper attempts to enhance the detection of diabetic based on set of attributes collected from the patients to develop a mathematical model using Multigene Symbolic Regression Genetic Programming technique. Genetic Programming (GP) showed significant advantages on evolving nonlinear model which can be used for prediction. The developed GP model is evaluated using Pima Indian data set and showed higher capability and accuracy in detection and diagnosis of Diabetes.",

}

Genetic Programming entries for Ahlam A Sharief Alaa Sheta

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