NDLI: Assessment of chronic kidney disease using skin texture as a key parameter: for South Indian population

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Assessment of chronic kidney disease using skin texture as a key parameter: for South Indian population

Content Provider	IET Digital Library
Author	Udhayarasu, Madhanlal Ramakrishnan, Kalpana Periasamy, Soundararajan
Abstract	Periodical monitoring of renal function, specifically for subjects with history of diabetic or hypertension would prevent them from entering into chronic kidney disease (CKD) condition. The recent increase in numbers may be due to food habits or lack of physical exercise, necessitates a rapid kidney function monitoring system. Presently, it is determined by evaluating glomerular filtration rate (GFR) that is mainly dependent on serum creatinine value and demographic parameters and ethnic value. Attempted here is to develop ethnic parameter based on skin texture for every individual. This value when used in GFR computation, the results are much agreeable with GFR obtained through standard modification of diet in renal disease and CKD epidemiology collaboration equations. Once correlation between CKD and skin texture is established, classification tool using artificial neural network is built to categorise CKD level based on demographic values and parameter obtained through skin texture (without using creatinine). This network when tested gives almost at par results with the network that is trained with demographic and creatinine values. The results of this Letter demonstrate the possibility of non-invasively determining kidney function and hence for making a device that would readily assess the kidney function even at home.
Starting Page	223
Ending Page	227
Page Count	5
Volume Number	4
e-ISSN	20533713
Issue Number	Issue 6, Dec (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/htl/4/6
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/htl.2016.0098
Journal	Healthcare Technology Letters
Publisher	The Institution of Engineering and Technology
Publisher Date	2017-05-23
Access Restriction	Open
Rights License	Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Subject Keyword	Artificial Neural Network Biological Organs Biomedical Engineering Chronic Kidney Disease CKD Epidemiology Collaboration Equation Diseases Glomerular Filtration Rate Health And Safety Aspects Healthcare Information Technology Application Neural Nets Skin Skin Texture South Indian Population
Content Type	Text
Resource Type	Article

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