Analyzing the machine learning for diagnosing chronic kidney disease

Author:

Hemalatha R.,Nathiyadevi K.,Ranganathan Hemalatha,Priya R.,Vanmathi P.

Publisher

AIP Publishing

Reference16 articles.

1. L. Jena and N. Ku. Kamila, “Distributed data mining classification algorithms for prediction of chronic-kidney-disease,” International Journal of Emerging Research in Management &Technology, vol. 4, Issue. 11, pp: 110–118, (2015).

2. A comparative study on thyroid disease detection using K-nearest neighbor and Naive Bayes classification techniques

3. S.B. Jagtap, “Census data mining and data analysis using WEKA,” arXiv preprint arXiv: 1310.4647, (2013).

4. S. Dilli Arasu, R. Thirumalaiselvi, “Review of Chronic Kidney Disease based on Data Mining Techniques,” International Journal of Applied Engineering Research, vol. 12, pp: 13498–13505, (2017).

5. S. Zeynu, Shruti Patil, “Survey on Prediction of Chronic Kidney Disease Using Data Mining Classification Techniques and Feature Selection,” International Journal of Pure and Applied Mathematics, vol. 118, No. 8, pp: 149–156, (2018).

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