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Analysis of Chronic Kidney Disease Using Machine Learning


Affiliations
1 Dept. of CS&E, Bapuji Institute of Engineering and Technology, Davangere-577004, Karnataka, India
2 Dept. of CS&E, Bapuji Institute of Engineering and Technology, Davangere-577004, Karnataka, India
     

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Chronic renal disease occurs when the kidneys in a person's body do not function properly for more than three months. Chronic Kidney Disease (CKD) is a serious medical condition that can be reversed if caught early. The properties of various medical tests are researched in order to determine which features may include disease-related information. According to the information, it aids in shaping the severity of the problem, the patient's expected survival after the sickness, the disease pattern, and effort to cure the sickness. Several machine learning algorithms have been developed to predict and assess chronic diseases such as renal, diabetes, cancer, and heart disease. Decision Tree (DT), SVM, ANN, linear Regression (LR), KNN, NB, and time series prediction models are the algorithms used.

Keywords

Chronic Kidney Disease, Decision Tree, Machine Learning, Biomedical, Healthcare.
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  • Analysis of Chronic Kidney Disease Using Machine Learning

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Authors

H. Pooja
Dept. of CS&E, Bapuji Institute of Engineering and Technology, Davangere-577004, Karnataka, India
Gaurav Soni
Dept. of CS&E, Bapuji Institute of Engineering and Technology, Davangere-577004, Karnataka, India

Abstract


Chronic renal disease occurs when the kidneys in a person's body do not function properly for more than three months. Chronic Kidney Disease (CKD) is a serious medical condition that can be reversed if caught early. The properties of various medical tests are researched in order to determine which features may include disease-related information. According to the information, it aids in shaping the severity of the problem, the patient's expected survival after the sickness, the disease pattern, and effort to cure the sickness. Several machine learning algorithms have been developed to predict and assess chronic diseases such as renal, diabetes, cancer, and heart disease. Decision Tree (DT), SVM, ANN, linear Regression (LR), KNN, NB, and time series prediction models are the algorithms used.

Keywords


Chronic Kidney Disease, Decision Tree, Machine Learning, Biomedical, Healthcare.

References