A Random Forest Classifier Combined with Missing Data Strategies for Predicting Chronic Kidney Disease Stages

Author:

Scoralick João P.ORCID,Iwashima Gabriele C.ORCID,Colugnati Fernando A. B.ORCID,Goliatt LeonardoORCID,Capriles Priscila V. S. Z.ORCID

Publisher

Springer Singapore

Reference19 articles.

1. Cao, Y., Hu, Z.D., Liu, X.F., Deng, A.M., Hu, C.J.: An mlp classifier for prediction of hbv-induced liver cirrhosis using routinely available clinical parameters. Dis. Markers 35(6), 653–60 (2013). http://orcid.org/10.1155/2013/127962

2. Cunningham, P., Delany, S.: k-nearest neighbour classifiers. Mult. Classif. Syst. (2007). https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.100.1131&rep=rep1&type=pdf

3. Dessai, I.S.F.: Intelligent heart disease prediction system using probabilistic neural network. Int. J. Adv. Comput. Theory Eng. (IJACTE) 2(3), 2319–2526 (2013). http://www.irdindia.in/journal_ijacte/pdf/vol2_iss3/8.pdf

4. Foundation, N.K.: Estimated glomerular filtration rate (egfr) (2020). https://www.kidney.org/atoz/content/gfr. Accessed 11 Oct 2020

5. Foundation, N.K.: Glomerular filtration rate calculator (2020). https://www.kidney.org/professionals/kdoqi/gfr_calculator. Accessed 30 Oct 2020

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