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Cited by 602

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Prediction of Heart Disease Using a Combination of Machine Learning and Deep Learning

Open access
Bharti, Rohit, Khamparia, Aditya, Shabaz, Mohammad, Dhiman, Gaurav, Pande, Sagar, Singh, Parneet·2021·Computational Intelligence and Neuroscience

Abstract

The correct prediction of heart disease can prevent life threats, and incorrect prediction can prove to be fatal at the same time. In this paper different machine learning algorithms and deep learning are applied to compare the results and analysis of the UCI Machine Learning Heart Disease dataset. The dataset consists of 14 main attributes used for performing the analysis. Various promising results are achieved and are validated using accuracy and confusion matrix. The dataset consists of some irrelevant features which are handled using Isolation Forest, and data are also normalized for getting better results. And how this study can be combined with some multimedia technology like mobile devices is also discussed. Using deep learning approach, 94.2% accuracy was obtained.

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Metadata

Authors
Bharti, R., Khamparia, A., Shabaz, M., Dhiman, G., Pande, S., & Singh, P.
Venue
Computational Intelligence and Neuroscience
Publisher
Wiley
Published
2021-01
Volume
2021
Issue
1
Pages
8387680-8387680
ISSN
  • 1687-5265 (ISSN-L)
  • 1687-5273
OpenAlex
W3177781640
Cited by
602
References
2
FWCI
91.26
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Prediction of Heart Disease Using a Combination of Machine Learning and Deep Learning. https://app.cochat.ai/papers/10.1155/2021/8387680
The paper
Bharti, R., Khamparia, A., Shabaz, M., Dhiman, G., Pande, S., & Singh, P. (2021). Prediction of Heart Disease Using a Combination of Machine Learning and Deep Learning. Computational Intelligence and Neuroscience. https://doi.org/10.1155/2021/8387680

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