Automated Chronic Kidney Disease Detection Model with Knearest Neighbor
نویسندگان
چکیده
منابع مشابه
Endocrine disorders in chronic kidney disease
Background and Objective: Endocrine disorders are common in patients with chronic kidney disease (CKD). The aim of the present study is reviewing available literature to give a deep understanding of complexities of endocrine disorders in chronic kidney disease. Methods: A narrative reviewing method based on the available literature was approached. Findings: Generally, when renal function de...
متن کاملEarly Detection of Progressive Chronic Kidney Disease
.............................................................................................................................................. ii ACKNOWLEDGEMENTS .......................................................................................................................... iii TABLE OF CONTENTS ............................................................................................
متن کاملChronic Kidney Disease: Detection and Evaluation.
Chronic kidney disease affects 47 million people in the United States and is associated with significant health care costs, morbidity, and mortality. Because this disease can silently progress to advanced stages, early detection is critical for initiating timely interventions. Multiple guidelines recommend at least annual screening with serum creatinine, urine albumin/creatinine ratio, and urin...
متن کاملEtiology and Outcome of Chronic Kidney Disease in Iranian Children
Background Considering the significant geographical and ethnical differences in pattern of incidence, etiology and outcome of chronic kidney disease (CKD), the present study aimed to assess the etiology and outcome of CKD in Iranian children. Materials and Methods In a cross-sectional study etiology and outcome of 372 children aged 3 months to 18 years with CKD was studied during the period 199...
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ژورنال
عنوان ژورنال: International Journal of Computer and Information Technology(2279-0764)
سال: 2021
ISSN: 2279-0764
DOI: 10.24203/ijcit.v10i3.110