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@article{160146,
        author = {Muni Giri Babu.E and Durga Sri.P and Bhumi Sri.P and Asif Ahamed.V and Mr. Narayan H.M},
        title = {Prediction Of Chronic Kidney Disease Using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {2},
        pages = {757-761},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=160146},
        abstract = {Chronic Kidney Disease is one of the most critical illness nowadays and proper diagnosis is required as soon as possible. Machine learning technique has become reliable for medical treatment. With the help of a machine learning classifier algorithms, the doctor can detect the disease on time. For this perspective, Chronic Kidney Disease prediction has been discussed in this article. Chronic Kidney Disease dataset has been taken from the Kaggle. Six classifier algorithms have been applied in this research such as SVM, XG Boost, Naïve bayes, logistic regression, random forest, decision tree. The important feature selection technique was also applied to the dataset.},
        keywords = {},
        month = {},
        }