Conference Paper2023

SMOTE Oversampling and near Miss Undersampling Based Diabetes Diagnosis from Imbalanced Dataset with XAI Visualization

Nasim Mahmud Nayan, Ashraful Islam, Muhammad Usama Islam, Eshtiak Ahmed, Mohammad Mobarak Hossain, Md Zahangir Alam

28th IEEE Symposium on Computers and Communications (ISCC)-ICT4eHealth

IEEE, pp. 1-6

DOI: 10.1109/iscc58397.2023.10218281URL

CCDS Authors

Ashraful Islam

Ashraful Islam, PhD

Center DirectorDirector, Human-Computer Interaction Wing

References

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  3. 3.J. Pradeep Kandhasamy, S. Balamurali. (2015). Performance Analysis of Classifier Models to Predict Diabetes Mellitus. Procedia Computer Science, 47, 45–51[10.1016/j.procs.2015.03.182]
  4. 4.Ronald J. Tallarida, Rodney B. Murray. (1987). Chi-Square Test. , 140–142[10.1007/978-1-4612-4974-0_43]
  5. 5.Show-Jane Yen, Yue‐Shi Lee. (2006). Under-Sampling Approaches for Improving Prediction of the Minority Class in an Imbalanced Dataset. Lecture notes in control and information sciences, 731–740[10.1007/978-3-540-37256-1_89]
  6. 6.N. Yuvaraj, K R SriPreethaa. (2017). Diabetes prediction in healthcare systems using machine learning algorithms on Hadoop cluster. Cluster Computing, 22(S1), 1–9[10.1007/s10586-017-1532-x]
  7. 7.Luis Fregoso-Aparicio, Julieta Noguez, Luis Montesinos, José Antonio García-García. (2021). Machine learning and deep learning predictive models for type 2 diabetes: a systematic review. Diabetology & Metabolic Syndrome, 13(1), 148[10.1186/s13098-021-00767-9]
  8. 8.S K Somasundaram, P. Alli. (2017). A Machine Learning Ensemble Classifier for Early Prediction of Diabetic Retinopathy. Journal of Medical Systems, 41(12), 201[10.1007/s10916-017-0853-x]
  9. 9.Pratya Nuankaew, Supansa Chaising, Punnarumol Temdee. (2021). Average Weighted Objective Distance-Based Method for Type 2 Diabetes Prediction. IEEE Access, 9, 137015–137028[10.1109/access.2021.3117269]
  10. 10.Manju Devi. (2016). ANALYSIS OF VARIOUS DATA MINING TECHNIQUES TO PREDICT DIABETES MELLITUS. , 11(1), 727–730
  11. 11.Muhammad Usama Islam, Md Mozaharul Mottalib, Mehedi Hassan, Zubair Ibne Alam, SM Zobaed, Md. Fazle Rabby. (2022). The Past, Present, and Prospective Future of XAI: A Comprehensive Review. Studies in computational intelligence, 1–29[10.1007/978-3-030-96630-0_1]
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