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The Early Prediction Acute Myocardial Infarction in Real-Time Data Using an Ensemble Machine Learning Model

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Advances in Intelligent Information Hiding and Multimedia Signal Processing

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 156))

Abstract

Cardiovascular disease is one of the extremely dangerous diseases in the world. Thus, the early detection of acute myocardial infarction is a critical model for patients and doctors. If the cardiovascular disease can make early detection, patients can prevent acute myocardial infarction. In this paper, we propose a machine learning ensemble approach for early detection of cardiac events on electronic health records (EHRs). The proposed ensemble approach combines a set of different classifier algorithms that are Random Forest, Decision Tree, Artificial Neural Network, K-Nearest Neighbors, and Support Vector Machine. Data from the Korea Acute Myocardial Infarction Registry (KAMIR), real life an acute myocardial database.

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Acknowledgements

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2017R1D1A1A02018718).

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Authors and Affiliations

  1. Department of Computer Science, College of Electrical and Computer Engineering, Chungbuk National University, Cheoungju City, 28644, South Korea

    Bilguun Jargalsaikhan, Muhammad Saqlain, Sherazi Syed Waseem Abbas, Moon Hyun Jae, In Uk Kang, Sikandar Ali & Jong Yun LEE

Authors
  1. Bilguun Jargalsaikhan
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  2. Muhammad Saqlain
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  3. Sherazi Syed Waseem Abbas
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  4. Moon Hyun Jae
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  5. In Uk Kang
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  6. Sikandar Ali
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  7. Jong Yun LEE
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Corresponding author

Correspondence to Jong Yun LEE .

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Editors and Affiliations

  1. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao Shi, Shandong, China

    Jeng-Shyang Pan

  2. Northeast Electric Power University, Chuanying Qu, Jilin, China

    Jianpo Li

  3. Swinburne University of Technology, Hawthorn, Melbourne, Australia

    Pei-Wei Tsai

  4. Centre for Artificial Intelligence, University of Technology Sydney, Sydney, NSW, Australia

    Lakhmi C. Jain

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Jargalsaikhan, B. et al. (2020). The Early Prediction Acute Myocardial Infarction in Real-Time Data Using an Ensemble Machine Learning Model. In: Pan, JS., Li, J., Tsai, PW., Jain, L. (eds) Advances in Intelligent Information Hiding and Multimedia Signal Processing. Smart Innovation, Systems and Technologies, vol 156. Springer, Singapore. https://doi.org/10.1007/978-981-13-9714-1_28

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