Diabetes Prediction Using Machine Learning

1. Azra Ramezankhani, Omid Pournik, Jamal Shahrabi, Fereidoun Azizi and Farzad Hadaegh, ”An Application of Association Rule Mining
to Extract Risk Pattern for Type 2 Diabetes Using Tehran Lipid and Glucose Study Database”, Int J Endocrinol Metab, April 2015.
2. Arora, R., Suman, 2012. Comparative Analysis of Classification Algorithms on Different Datasets using WEKA. International Journal of
Computer Applications 54, 21–25. doi:10.5120/8626-2492.
3. Rani, A. S., & Jyothi, S. (2016, March). Performance analysis of classification algorithms under different datasets. In Computing for
Sustainable Global Development (INDIACom), 2016 3rd International Conference on (pp. 1584- 1589). IEEE
4. Choubey, D.K., Paul, S., Kumar, S., Kumar, S., 2017. Classification of Pima indian diabetes dataset using naive bayes with genetic
algorithm as an attribute selection, in: Communication and Computing Systems: Proceedings of the International Conference on
Communication and Computing System (ICCCS 2016), pp. 451– 455
5. M. F. Faruque, Asaduzzaman and I. H. Sarker, ”Performance Analysis of Machine Learning Techniques to Predict Diabetes Mellitus”,
2019 International Conference on Electrical Computer and Communication Engineering (ECCE), pp. 1-4, 2019.