Optimizing Heart Disease Prediction Models through SMOTE: Addressing Data Imbalance-Reference-Cited by-同舟云学术

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Optimizing Heart Disease Prediction Models through SMOTE: Addressing Data Imbalance

Published:2024-08-06 Issue: Volume: Page:1-10
ISSN:
Container-title:2024 4th International Conference on Emerging Smart Technologies and Applications (eSmarTA)
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Author:

Baddah Waheeb¹,Qasem Hamzah Ali²,Alsabry Ayman³,Al Gawani Rana Saleh⁴,Alzuraiqi Wafa Mohammed³,Hanash F. E.⁵

Affiliation:

1. Azal University for Human Development, International University of Technology Twintech,Sana’a,Yemen

2. International University of Technology Twintech, 21 September University of Medical and Applied Sciences,Sana’a,Yemen

3. International University of Technology Twintech,Department of Computer Science,Sana’a,Yemen

4. Lebanese International University,Sana’a,Yemen

5. Emirates International University, International University of Technology Twintech,Sana’a,Yemen

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10638789/10638835/10638899.pdf?arnumber=10638899

Reference26 articles.

1. Predicting Heart Disease Using Machine Learning Techniques on Electronic Health Records Data

2. Machine Learning Techniques for Heart Disease Prediction: A Comparative Study and Analysis

3. Heart Diseases Prediction using Machine Learning

4. An Effective Machine Learning-Based Model for an Early Heart Disease Prediction

5. Iterative Tuning of Tree-Ensemble-Based Models' parameters Using Bayesian Optimization for Breast Cancer Prediction

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