The effect of Data Augmentation Using SMOTE: Diabetes Prediction by Machine Learning Techniques-Reference-Cited by-同舟云学术

The effect of Data Augmentation Using SMOTE: Diabetes Prediction by Machine Learning Techniques

Published:2023-12-16 Issue: Volume:2 Page:13-20
ISSN:
Container-title:2023 6th Artificial Intelligence and Cloud Computing Conference (AICCC)
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Author:

Al-Qerem A.¹^ORCID,Ali A. M²^ORCID,Alauthman M.³^ORCID,Khaldy M. Al⁴^ORCID,Aldweesh A.⁵^ORCID

Affiliation:

1. Computer Science Department, Faculty of Information Technology, Zarqa University, Jordan

2. Communications and Computer Engineering Department, Faculty of Engineering, Al-Ahliyya Amman University, Jordan

3. Department of Information Security, Faculty of Information Technology, University of Petra, Jordan

4. Business Inteligence & Data Analytics, University of Petra, Jordan

5. College of Computing and Information Technology, Shaqra University, Saudi Arabia

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3639592.3639595

Reference17 articles.

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2. A new classwise k nearest neighbor (CKNN) method for the classification of diabetes dataset;Christobel Y. A.;International Journal of Engineering and Advanced Technology,2013

3. Farahmandian, M., Lotfi, Y., & Maleki, I. (2015). Data mining algorithms application in diabetes diseases diagnosis: A case study. vol, 3, 989-997.‏

4. Alauthman M Al-qerem A Sowan B Alsarhan A Eshtay M Aldweesh A Aslam N. Enhancing Small Medical Dataset Classification Performance Using GAN. Informatics. 2023; 10(1):28.

5. Alauthman M Aldweesh A Al-qerem A Aburub F Al-Smadi Y Abaker AM Alzubi OR Alzubi B. Tabular Data Generation to Improve Classification of Liver Disease Diagnosis. Applied Sciences. 2023; 13(4):2678.‏