HIGHLIGHTS
- who: Zahid Ullah from the Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia have published the research work: EarlyDetectionandDiagnosisofChronicKidneyDiseaseBasedon Selected Predominant Features, in the Journal: Journal of Healthcare Engineering of 30/01/2023
- what: The study of Gudeti et_al aimed to diagnose CKD at an early stage, and as a result, they trained SVM, KNN, and LR models, which achieved accuracy rates of 99.25%, 78.75%, and 77.25%, respectively. Terefore, this study has used the practice of cross-validation of 10 folds for each model . . .
If you want to have access to all the content you need to log in!
Thanks :)
If you don't have an account, you can create one here.