Prediction model using SMOTE, genetic algorithm and decision tree (PMSGD) for classification of diabetes mellitus
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Information Systems,Software
Link
https://link.springer.com/content/pdf/10.1007/s00530-021-00817-2.pdf
Reference63 articles.
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2. Domingueti, C.P., Dusse, L.M., Carvalho, M.D., Sousa, L.P., Gomes, K.B., Fernandes, A.P.: Diabetes mellitus: the linkage between oxidative stress, inflammation, hypercoagulability and vascular complications. J. Diabetes Complicat. 30(4), 738–745 (2016). https://doi.org/10.1016/j.jdiacomp.2015.12.018
3. World health organization statistics on diabetes. http://www.who.int/mediacentre/factsheets/fs312/en/. Accessed 02 Mar 2020
4. Pham, H.N., Triantaphyllou, E.: Prediction of diabetes by employing a new data mining approach which balances fitting and generalization. Comput. Inf. Sci. Stud. Comput. Intell. (2008). https://doi.org/10.1007/978-3-540-79187-4_2
5. Wild, S., Roglic, G., Green, A., Sicree, R., King, H.: Global prevalence of diabetes: estimates for the year 2000 and projections for 2030. Diabetes Care 27(5), 1047–1053 (2004). https://doi.org/10.2337/diacare.27.5.1047
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