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Addressing Concept Drifts Using Deep Learning for Heart Disease Prediction: A Review

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Proceedings of Second Doctoral Symposium on Computational Intelligence

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1374))

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Abstract

Heart disease is definitely among the many most significant triggers of morbidity and fatality amid the populace among the globe. Prediction of cardiac disease can be considered as one particular among the most crucial topics in the sector of medical info evaluation. The quantity of data through the medical industry is very large. Deep learning becomes the huge range of natural medical care data straight to data which usually may support to identify possibilities and forecasts. This paper reveals the novel algorithm and performance methodology that can forecast the heart disease by ways of CNN modeling. The parameters evaluation will be done for accuracy, sensitivity, specificity, and positive prediction value (PPV). Such parameters can be used in a user-friendly manner by doctors to trace out the possibility of diseases.

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Authors and Affiliations

  1. PCET’s Pimpri Chinchwad College of Engineering, Pune, India

    Ketan Sanjay Desale & Swati V. Shinde

Authors
  1. Ketan Sanjay Desale
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  2. Swati V. Shinde
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Corresponding author

Correspondence to Ketan Sanjay Desale .

Editor information

Editors and Affiliations

  1. Department of Computer Science Engineering, Maharaja Agrasen Institute of Technology, Rohini, Delhi, India

    Deepak Gupta

  2. Maharaja Agrasen Institute of Technology, Rohini, Delhi, India

    Ashish Khanna

  3. Institute of Engineering and Technology, Lucknow, Uttar Pradesh, India

    Vineet Kansal

  4. University of Calabria, Rende, Cosenza, Italy

    Giancarlo Fortino

  5. Department of Information Technology, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

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Desale, K.S., Shinde, S.V. (2022). Addressing Concept Drifts Using Deep Learning for Heart Disease Prediction: A Review. In: Gupta, D., Khanna, A., Kansal, V., Fortino, G., Hassanien, A.E. (eds) Proceedings of Second Doctoral Symposium on Computational Intelligence . Advances in Intelligent Systems and Computing, vol 1374. Springer, Singapore. https://doi.org/10.1007/978-981-16-3346-1_13

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