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research article
Diabetes Prediction Using Machine Learning
V.V.Kalunge1
Kalpesh Sonawane2
Rohan Bhonsle3
Saurav More4
Nikita Bhosle5
1Professor, Department of Information Technology, JSPM’S Jayawantrao Sawant College of Engineering, Hadapsar, pune, India. 2345Department of Information Technology, JSPM’S Jayawantrao Sawant College of Engineering, Hadapsar, pune, India.
Published Online: May-June 2023
Pages: 571-574
Cite this article
↗ https://www.doi.org/10.59256/ijire.20230403121
References
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.
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.
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