J Renal Inj Prev. 2017;6(2): 83-87. doi: 10.15171/jrip.2017.16
PMID: 28497080        PMCID: PMC5423289

Original Article

Applying data mining techniques to determine important parameters in chronic kidney disease and the relations of these parameters to each other

Cited by CrossRef: 2

1- Lajoie P, Gaudreault J, Lehoux N, Ali M. A data-driven framework to deal with intrinsic variability of industrial processes: An application in the textile industry. IFAC-PapersOnLine. 2019;52(13):731 [Crossref]
2- Murshid G, Parvez T, Fezal N, Azaz L, Asif M. Data Mining Techniques to Predict Chronic Kidney Disease. IJSRCSEIT. 2019;:1220 [Crossref]
3- Sahu S, Shrivas A. Comparative Study of Classification Models with Genetic Search Based Feature Selection Technique. 2018;9(3):1 [Crossref]