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Heart Attack Classification System Using Neural Network Trained with Particle Swarm Optimization

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Proceedings of the ICR’22 International Conference on Innovations in Computing Research (ICR 2022)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1431))

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Abstract

The prior detection of a heart attack could lead to the saving of one’s life. Putting specific criteria into a system that provides an early warning of an imminent attack will be advantageous to a better prevention plan for an upcoming heart attack. Some studies have been conducted for this purpose, but yet the goal has not been reached to prevent a patient from getting such a disease. In this paper, Neural Network trained with Particle Swarm Optimization (PSONN) is used to analyze the input criteria and enhance heart attack anticipation. A real and novel dataset that has been recorded on the disease is used. After preprocessing the data, the features are fed into the system. As a result, the outcomes from PSONN have been evaluated against those from other algorithms. Decision Tree, Random Forest, Neural network trained with Backpropagation (BPNN), and Naive Bayes were among those employed. Then the results of 100%, 99.2424%, 99.2323%, 81.3131%, and 66.4141% are produced concerning the mentioned algorithms, which show that PSONN has recorded the highest accuracy rate among all other tested algorithms.

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Author information

Authors and Affiliations

  1. Technical College of Informatics, Sulaimani Polytechnic University, Sulaimani, KRG, Iraq

    Askandar H. Amin

  2. Administration and Economics, University of Sulaimani, Sulaimani, KRG, Iraq

    Botan K. Ahmed

  3. IT Department, College of Commerce, University of Sulaimani, Sulaimani, KRG, Iraq

    Bestan B. Maaroof

  4. School of Information Technology, Fanshawe College, London, Canada

    Bestan B. Maaroof

  5. Computer Science and Engineering Department, University of Kurdistan Hewler, Erbil, KRG, Iraq

    Tarik A. Rashid

Authors
  1. Askandar H. Amin
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  2. Botan K. Ahmed
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  3. Bestan B. Maaroof
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  4. Tarik A. Rashid
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Corresponding author

Correspondence to Askandar H. Amin .

Editor information

Editors and Affiliations

  1. University of Detroit Mercy, Detroit, MI, USA

    Kevin Daimi

  2. Kent Institute Australia, Sydney, NSW, Australia

    Abeer Al Sadoon

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Amin, A.H., Ahmed, B.K., Maaroof, B.B., Rashid, T.A. (2022). Heart Attack Classification System Using Neural Network Trained with Particle Swarm Optimization. In: Daimi, K., Al Sadoon, A. (eds) Proceedings of the ICR’22 International Conference on Innovations in Computing Research. ICR 2022. Advances in Intelligent Systems and Computing, vol 1431. Springer, Cham. https://doi.org/10.1007/978-3-031-14054-9_4

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