A Medical Decision Support System based on Genetic Algorithm and Least Square Support Vector Machine for Diabetes Disease Diagnosis

Abstract

 Clinical decision making is a complex task for physicians since it requires the utmost accuracy of diagnosis. This paper proposes a medical decision support system based on Genetic Algorithm and Least Square Support Vector Machine (LS-SVM) for the diagnosis of diabetes on a Pima Indian Diabetes dataset of UCI machine learning repository. The proposed system uses Genetic algorithm selects a more significant feature subset from the given feature set of the dataset and uses Least Square Support Vector Machine (LS-SVM) for The results show the classification accuracy of the proposed system outperforms that of various existing systems. The performance of the proposed system is analyzed using various parameters like classification accuracy, using 10-fold crossvalidation and confusion matrix.

Authors and Affiliations

Aishwarya S*

Keywords

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  • EP ID EP138000
  • DOI -
  • Views 54
  • Downloads 0

How To Cite

Aishwarya S* (30).  A Medical Decision Support System based on Genetic Algorithm and Least Square Support Vector Machine for Diabetes Disease Diagnosis. International Journal of Engineering Sciences & Research Technology, 3(4), 4042-4046. https://europub.co.uk/articles/-A-138000