Diagnosis of Chronic Kidney Disease Using Various Features

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Sena Goral


The development of technology provides great convenience in the field of medicine, as in every field. Analyzing the patient's personal information with modern techniques allows specialists to perform faster and more effective treatment. In this study, data with 24 attributes obtained from laboratory results of 400 patients were classified and compared with KNN, decision tree classifier, random forest classifier and adaboost classifier. As a result of classification, Ada Boost Classifier showed the best performance with score value of 98.3%.

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GORAL, Sena. Diagnosis of Chronic Kidney Disease Using Various Features. Journal of Multidisciplinary Developments, [S.l.], v. 7, n. 1, p. 16-22, mar. 2022. ISSN 2564-6095. Available at: <http://jomude.com/index.php/jomude/article/view/102>. Date accessed: 24 apr. 2024.
Natural Sciences - Regular Research Paper


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