Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Reference :

    1. Neelamadhab Padhy, Dr. Pragnyaban Mishra and Rasmita Panigrahi, “The Survey of Data Mining Applications and Feature Scope,” International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), 2(3), pp 43-58, 2012.
    2. J.C. Prather, D. F. Lobach, L. K. Goodwin, J. W. Hales, M. L. Hage, and W. E. Hammond, “Medical data mining: knowledge discovery in a clinical data warehouse,” Proceedings of the AMIA Annual Fall Symposium, pp 101–105, 1997.
    3. Subhash Chandra Pandey, “Data mining techniques for medical data: A review,” International Conference on Signal Processing, Communication, Power and Embedded System, Paralakhemundi, India, pp 972-982, 2016.
    4. H. Polat, H. D. Mehr, and A. Cetin, “Diagnosis of Chronic Kidney Disease Based on Support Vector Machine by Feature Selection Methods,” J. Med. Syst., Vol. 41, no. 4, Apr. 2017.
    5. K. Chandel, V. Kunwar, S. Sabitha, T. Choudhury, and S. Mukherjee, “A Comparative study on thyroid disease detection using K-nearest neighbor and Naive Bayes classification techniques,” CSI Trans. ICT, Vol. 4, no. 2–4, pp. 313–319, Dec. 2016.
    6. Vijayarani, S. and Dhayanand, S., “Data mining classification algorithms for kidney disease prediction”, Int. J. Cybern. Inf. (IJCI), Vol. 4, No. 4, pp 13–25, 2015. A. R. Shetty, F. B. Ahmed, V. M. Naik, “CKD Prediction Using Data Mining Technique as SVM and KNN with Pycharm”, International Research Journal of Engineering and Technology, Vol. 6, No. 5, pp 4399-4405, 2019.
    7. S. Tekale, S. Pranjal, S. Wandhekar, A. Chatorikar, “Prediction of Chronic Kidney Disease Using Machine Learning Algorithm”, International Journal of Advanced Research in Computer and Communication Engineering, Vol. 7, No. 10, pp 92-96, 2018
    8. G. Kaur, A. Sharma, “Predict Chronic Kidney Disease using Data Mining Algorithms in Hadoop”, International Journal of Engineering Researches and Management Studies, Vol. 5, No. 2, pp 34-48, 2018.
    9. S. Vijayarani, S. Dhayanand, “Kidney Disease Prediction using SVM and ANN Algorithms”, International Journal of Computing and Business Research, Vol. 6, No. 2, 2015.
    10. A. Charleonnan, T. Fufaung, T. Niyomwong, W. Chokchueypattanakit, S. Suwannawach, N. Ninchawee, “Predictive Analytics for Chronic Kidney Disease using Machine Learning Techniques”, IEEE International Conference on Management and Innovation Technology, 2016
    11. Z. Chen, X. Zhang, Z. Zhang, “Clinical risk assessment of patients with chronic kidney disease by using clinical data and multivariate models”, Int. Urol. Nephrol., Vol. 48, No. 12, pp 2069–2075, 2016.

Recent Article