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All Journal International Journal of Basic and Applied Science
Frank H.
N.P.A. Rockville, USA
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Physics

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Exploring the role of urine analysis in early detection of chronic kidney disease Frank H.
International Journal of Basic and Applied Science Vol. 12 No. 1 (2023): June: Basic and Applied Science
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/ijobas.v12i1.248

Abstract

This study focuses on the development and validation of a urine-based diagnostic model for early detection of Chronic Kidney Disease (CKD). Only urine indicators, hypertension, diabetes mellitus, coronary artery disease, appetite, pedal edema, and anemia, are selected based on their relevance to CKD. A decision tree algorithm is utilized for model development, with specific parameters set for optimal performance. The model is trained and evaluated using two datasets, demonstrating promising results in terms of 100% true positive and true negative rates in validation study. The findings highlight the potential clinical significance and applicability of the developed model for timely interventions in CKD patients.
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