Peck, S.M. and Hua, N.T. and Seyed, M.M. (2016) Classification of urinary dielectric properties for diabetes and kidney disease using support vector machine. In: The 16th International Conference on Biomedical Engineering 2016, 7-10 December 2016, Singapore.
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Abstract
This paper classifies the urinary dielectric properties of subjects with diabetes mellitus (DM), chronic kidney disease (CKD), and normal subjects at microwave frequency from 1 GHz to 50 GHz using support vector machine (SVM). The dielectric properties measurements were conducted using open-ended coaxial probe at room temperature (25°C), 30°C and human body temperature (37°C). The highest classification accuracy was achieved at 88.72% to distinguish diabetic subjects from normal. The urinary dielectric behavior was found optimal at 30°C. The highest accuracy was achieved at 64.50% for three-group classification.
Item Type: | Conference or Workshop Item (Paper) |
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Funders: | UNSPECIFIED |
Additional Information: | Conference paper - MST |
Uncontrolled Keywords: | Urinary dielectric properties; Diabetes and kidney disease; Support vector machine |
Subjects: | R Medicine > R Medicine (General) T Technology > TA Engineering (General). Civil engineering (General) |
Divisions: | Faculty of Engineering |
Depositing User: | Mr. Mohd Safri |
Date Deposited: | 11 Jan 2017 08:40 |
Last Modified: | 16 Jan 2017 03:02 |
URI: | http://eprints.um.edu.my/id/eprint/16826 |
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