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Kahramanli, H. and Allahverdi, N.(2008) Design of a Hybrid System for the Diabetes and Heart Diseases. Expert Systems with Applications, 35, 82-89.
http://dx.doi.org/10.1016/j.eswa.2007.06.004

has been cited by the following article:

  • TITLE: A Hybrid ANN-GWO Algorithm for Prediction of Heart Disease

    AUTHORS: Hamza Turabieh

    KEYWORDS: Artificial Neural Network, Gray Wolf Optimizer, Back-Propagation, Heart Disease

    JOURNAL NAME: American Journal of Operations Research, Vol.6 No.2, March 8, 2016

    ABSTRACT: The paper investigates the powerful of hybridizing two computational intelligence methods viz., Gray Wolf Optimization (GWO) and Artificial Neural Networks (ANN) for prediction of heart disease. Gray wolf optimization is a global search method while gradient-based back propagation method is a local search one. The proposed algorithm implies the ability of ANN to find a relationship between the input and the output variables while the stochastic search ability of GWO is used for finding the initial optimal weights and biases of the ANN to reduce the probability of ANN getting stuck at local minima and slowly converging to global optimum. For evaluation purpose, the performance of hybrid model (ANN-GWO) was compared with standard back-propagation neural network (BPNN) using Root Mean Square Error (RMSE). The results demonstrate that the proposed model increases the convergence speed and the accuracy of prediction.