Classification of urinary dielectric properties for diabetes and kidney disease using support vector machine

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)
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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