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Heart Disease Prediction Using Core Machine Learning Techniques—A Comparative Study

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Advances in Data and Information Sciences

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 318))

Abstract

Cardiovascular diseases are responsible for twenty five per cent of the deaths in India and across the world. Indians are affected by CVDs at a much earlier age compared to the other demographics. Given the severity of the situation an early prediction of heart disease is of utmost importance. Heart diseases can be determined using a combination of clinical and pathological data. Often the volume of these data is too vast for the human brain to compute. Hence, we use machine learning algorithms to predict heart disease in human beings using the above mentioned data. This paper is concerned with the comparison of the various models and to determine which one of them is best suited for the prediction. The models used in this paper are Logistic Regression, Decision tree, Naive Bayes, SVM, K-Nearest Neighbours and Random Forest. It was found that logistic regression performed best with the accuracy of 85.25%.

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Author information

Authors and Affiliations

  1. School of Computer Engineering, KIIT Deemed to be University, Bhubaneswar, Odisha, 751024, India

    Sfurti Sarah, Mahendra Kumar Gourisaria, Sandali Khare & Himansu Das

Authors
  1. Sfurti Sarah
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  2. Mahendra Kumar Gourisaria
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  3. Sandali Khare
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  4. Himansu Das
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Editor information

Editors and Affiliations

  1. Krishna Engineering College, Ghaziabad, India

    Shailesh Tiwari

  2. National Institute of Technology Agartala, Agartala, Tripura, India

    Munesh C. Trivedi

  3. Department of Engineering and Science, University of Agder, Kristiansand, Norway

    Mohan Lal Kolhe

  4. Motilal Nehru National Institute of Technology, Allahabad, Uttar Pradesh, India

    K.K. Mishra

  5. Department of Computer Science and Engineering, RBS Engineering Technical Campus, Agra, Uttar Pradesh, India

    Brajesh Kumar Singh

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© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Sarah, S., Gourisaria, M. ., Khare, S., Das, H. (2022). Heart Disease Prediction Using Core Machine Learning Techniques—A Comparative Study. In: Tiwari, S., Trivedi, M.C., Kolhe, M.L., Mishra, K., Singh, B.K. (eds) Advances in Data and Information Sciences. Lecture Notes in Networks and Systems, vol 318. Springer, Singapore. https://doi.org/10.1007/978-981-16-5689-7_22

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