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Information Journal Paper

Title

Intelligent application for Heart disease detection using Hybrid Optimization algorithm

Pages

  15-27

Abstract

 Prediction of heart disease is very important because it is one of the causes of death around the world. More-over, heart disease prediction in the early stage plays a main role in the treatment and recovery disease and reduces costs of diagnosis disease and side e ects it. Ma-chine learning algorithms are able to identify an e ective pattern for diagnosis and treatment of the disease and identify e ective factors in the disease. this paper is in-vestigated a new hybrid algorithm of Whale Optimiza-tion and Dragon y algorithm using a machine learning algorithm. the hybrid algorithm employs a Support Vec-tor Machine algorithm for e ective Prediction of heart disease. Proposed method is evaluated by Cleveland standard heart disease dataset. The experimental re-sult indicates that the SVM accuracy of 88. 89 % and nine features are selected in this respect.

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    APA: Copy

    ESKANDARI, MARZIYEH, & Hassani, Zeinab. (2019). Intelligent application for Heart disease detection using Hybrid Optimization algorithm. JOURNAL OF ALGORITHMS AND COMPUTATION, 51(1), 15-27. SID. https://sid.ir/paper/354573/en

    Vancouver: Copy

    ESKANDARI MARZIYEH, Hassani Zeinab. Intelligent application for Heart disease detection using Hybrid Optimization algorithm. JOURNAL OF ALGORITHMS AND COMPUTATION[Internet]. 2019;51(1):15-27. Available from: https://sid.ir/paper/354573/en

    IEEE: Copy

    MARZIYEH ESKANDARI, and Zeinab Hassani, “Intelligent application for Heart disease detection using Hybrid Optimization algorithm,” JOURNAL OF ALGORITHMS AND COMPUTATION, vol. 51, no. 1, pp. 15–27, 2019, [Online]. Available: https://sid.ir/paper/354573/en

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