Early stage of chronic kidney disease by using statistical evaluation of the previous measurement results

Abstract Chronic kidney disease (CKD) that causes the progressive losses in kidney functions is one of the major public health problems. Expert medical doctors can diagnose the CKD through symptoms, blood and urine tests in its early stages. However, the diagnosis of CKD might be difficult for exper...

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Bibliographic Details
Published in:Biocybernetics and biomedical engineering 2016, Vol.36 (4), p.626-631
Main Author: Akben, Selahaddin Batuhan
Format: Article
Language:English
Subjects:
Advanced Basic Science
Chronic kidney disease
Chronic renal failure
CKD
Internal Medicine
Signal processing
Statistical evaluation
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Summary:Abstract Chronic kidney disease (CKD) that causes the progressive losses in kidney functions is one of the major public health problems. Expert medical doctors can diagnose the CKD through symptoms, blood and urine tests in its early stages. However, the diagnosis of CKD might be difficult for expert medical doctors in case of the questionable measurement result. Therefore a new mathematical method that would be helpful to the expert medical doctors is required. It can be said that there is no studies related with automatic diagnosis of CKD in the literature. This study aims to remedy this shortcoming in the literature. In this study, for each of test and symptom values, averages of measurement results were calculated separately for healthy subjects and patients. Then the measured values were marked as “0” or “1” (healthy or patient) according to closeness to average values. Finally, the classification was performed by averaging the values marked for each subject. The success rate of the proposed method is between 96% and 98% according to the age ranges. In conclusion section of the study, how to implement the proposed method in real life is offered.
ISSN:0208-5216
DOI:10.1016/j.bbe.2016.08.004