Chronic kidney disease stage classification using renal artery doppler-derived parameters

Munkhjargal Gochoo, Jun Wei Hsieh, Chien Hung Lee, Yun Chih Chen, Yu Chi Shih

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In renal medicine, Estimated Glomerular Filtration Rate (eGFR) based method is a standard for the diagnosis of chronic kidney disease. However, this method is invasive, uncomfortable, costly, and could be dangerous because it requires to draw blood from the artery vessels. Researchers have developed several non-invasive Doppler-derived measures based chronic kidney disease (CKD) stage diagnosing or prognosing approaches; however, there is no adequate automatic renal artery Doppler-derived CKD stage classification method in the literature. Thus, we propose a non-invasive, safer, faster, and low cost, SVM-based CKD stage classification method from a sonogram of the renal artery blood flow. The proposed method extracts kurtosis and curvature parameters of the probability distribution that generated from renal artery blood flow waveform. Kurtosis and curvatures are employed to measure the tailedness and curvedness of the probability distribution. We collected a total of 528 sonograms from 110 (49 males) CKD patients during 2010-2013. The experimental results revealed a statistically significant correlation between the parameters and CKD progress stages. Post-voting results revealed the best f1score of 0.956 for Positive (stages 1-5) CKD stages.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2502-2505
Number of pages4
ISBN (Electronic)9781728145693
DOIs
StatePublished - Oct 2019
Event2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019 - Bari, Italy
Duration: 6 Oct 20199 Oct 2019

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Volume2019-October
ISSN (Print)1062-922X

Conference

Conference2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019
CountryItaly
CityBari
Period6/10/199/10/19

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  • Cite this

    Gochoo, M., Hsieh, J. W., Lee, C. H., Chen, Y. C., & Shih, Y. C. (2019). Chronic kidney disease stage classification using renal artery doppler-derived parameters. In 2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019 (pp. 2502-2505). [8913899] (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics; Vol. 2019-October). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SMC.2019.8913899