Facebook pixel tracking

The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

Contact Info
Website thesai.org
Follow Us
Contact Info
Follow Us
Research Article | Open Access |

Developing a Mathematical Model to Detect Diabetes Using Multigene Genetic Programming

Author 1: Ahlam A Sharief Author 2: Alaa Sheta
International Journal of Advanced Research in Artificial Intelligence (IJARAI) · Vol. 3, No. 10 · Published 2014 · Cited by 28

DOI: 10.14569/IJARAI.2014.031007

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.

Keywords

How to Cite this Article

Sharief, A. A., & Sheta, A. (2014). Developing a Mathematical Model to Detect Diabetes Using Multigene Genetic Programming. International Journal of Advanced Research in Artificial Intelligence, 3(10). https://doi.org/10.14569/IJARAI.2014.031007

Sharief, Ahlam A, and Alaa Sheta. "Developing a Mathematical Model to Detect Diabetes Using Multigene Genetic Programming." International Journal of Advanced Research in Artificial Intelligence, vol. 3, no. 10, 2014, https://doi.org/10.14569/IJARAI.2014.031007.

@article{Sharief2014,
  title     = {Developing a Mathematical Model to Detect Diabetes Using Multigene Genetic Programming},
  journal   = {International Journal of Advanced Research in Artificial Intelligence},
  volume    = {3},
  number    = {10},
  year      = {2014},
  publisher = {The Science and Information Organization},
  author    = {Ahlam A Sharief and Alaa Sheta},
  doi       = {10.14569/IJARAI.2014.031007},
  url       = {https://doi.org/10.14569/IJARAI.2014.031007}
}

Open Access — licensed under a Creative Commons Attribution 4.0 International License. Unrestricted use, distribution, and reproduction in any medium, even commercially, as long as the original work is properly cited.

IJARAI Journal Cover