Abstract: Diabetes is a long-term disease. Inappropriate blood sugar level control in diabetic patients can lead to serious issues like kidney and heart diseases. Obesity is widely regarded as a major risk factor for type 2 diabetes. In this research, a model proposed to predict diabetic obese patients based on Expectation Maximization, PCA, and SMOTE Algorithms in the preprocessing and feature extraction phases, and using Fuzzy KNN classifier in the prediction phase. The model applied on real dataset and the accuracy of prediction results reflects the positive effect of the preprocessing techniques. The accuracy of the proposed model is 95.97% and outperforms other model applied on the same dataset.

Ibrahim Eldesouky Fattoh and Soha Safwat, “Prediction of Diabetic Obese Patients using Fuzzy KNN Classifier based on Expectation Maximization, PCA and SMOTE Algorithms” International Journal of Advanced Computer Science and Applications(IJACSA), 13(1), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130128

@article{Fattoh2022,
title = {Prediction of Diabetic Obese Patients using Fuzzy KNN Classifier based on Expectation Maximization, PCA and SMOTE Algorithms},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130128},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130128},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {1},
author = {Ibrahim Eldesouky Fattoh and Soha Safwat}
}