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Prediction of Heart Disease Using Deep Convolutional Neural Networks

  • Research Article-Computer Engineering and Computer Science
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Abstract

Heart diseases are currently a major cause of death in the world. This problem is severe in developing countries in Africa and Asia. A heart disease predicted at earlier stages not only helps the patients prevent it, but I can also help the medical practitioners learn the major causes of a heart attack and avoid it before its actual occurrence in patient. In this paper, we propose a method named CardioHelp which predicts the probability of the presence of cardiovascular disease in a patient by incorporating a deep learning algorithm called convolutional neural networks (CNN). The proposed method is concerned with temporal data modeling by utilizing CNN for HF prediction at its earliest stage. We prepared the heart disease dataset and compared the results with state-of-the-art methods and achieved good results. Experimental results show that the proposed method outperforms the existing methods in terms of performance evaluation metrics. The achieved accuracy of the proposed method is 97%.

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Authors and Affiliations

  1. Department of Computer Science, University of Engineering and Technology, Taxila, Pakistan

    Awais Mehmood, Munwar Iqbal, Aun Irtaza, Marriam Nawaz, Tahira Nazir & Momina Masood

  2. Department of Computer Engineering, University of Engineering and Technology, Taxila, Pakistan

    Zahid Mehmood

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  1. Awais Mehmood
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  2. Munwar Iqbal
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  3. Zahid Mehmood
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  4. Aun Irtaza
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  5. Marriam Nawaz
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  6. Tahira Nazir
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  7. Momina Masood
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All the authors contributed equally to this work.

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Correspondence to Tahira Nazir.

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Mehmood, A., Iqbal, M., Mehmood, Z. et al. Prediction of Heart Disease Using Deep Convolutional Neural Networks. Arab J Sci Eng 46, 3409–3422 (2021). https://doi.org/10.1007/s13369-020-05105-1

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  • DOI: https://doi.org/10.1007/s13369-020-05105-1

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