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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2020.10
- 수록면
- 1,394 - 1,397 (4page)
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초록· 키워드
오류제보하기
The urine test used as a basic test method of in vitro diagnosis for health care has been used for a long time to be simple and convenient. The urine test method is using a color that appears depending on the change in the ion concentration that reacts over time buried in the standard color test paper(Strips) with a urine sample applied to some reaction reagents. In this paper, it was proposed a neural network algorithm to obtain a suitable and reproducibility and accuracy classifier suitable for the urine analysis system. The experimental results were compared with the visual colorimetric analysis, and the neural network algorithm showed better results.
목차
ABSTRACT
Ⅰ. 서론
Ⅱ. 본론
Ⅲ. 실험 결과 및 고찰
Ⅳ. 결론
REFERENCES
참고문헌 (7)
참고문헌 신청
R. F. Rahmat, Royananda, M. A. Muchtar, R. Taqiuddin, S. Adnan, R. Anugrahwaty, and R. Budiarto, “Automated color classification of urine dipstick image in urine examination,” 2nd International Conference on Computing and Applied Informatics 2017, IOP Conf. Series: Journal of Physics: Conf. Series 978 012008, pp. 1-8, 2018. doi :10.1088/1742-6596/978/1/012008.
A. A. H.Gadalla, I. M. Friberg, A. Kift-Morgan, J. Zhang, M. Eberl, N. Topley, I. Weeks, S. Cuff, M. Wootton, M. Gal, G. Parekh, P. Davis, C. Gregory, K. Hood, K. Hughes, C. Butler, and N. A. Francis, “Identifcation of clinical and urine biomarkers for uncomplicated urinary tract infection using machine learning algorithms,” Scientific Reports(2019) 9:19694, pp. 1-11, Dec. 2019. doi.org/10.1038/s41598?019-55523-x.
A. Pouliakis, E. Karakitsou, N. Margari, P. Bountris, M. Haritou, J. Panayiotides, D. Koutsouris, and P. Karakitsos, “Artificial Neural Networks as Decision Support Tools in Cytopathology: Past, Present, and Future,” Biomedical Engineering and Computational Biology, 2016:7, pp. 1-18, Jan. 2016. doi:10.4137/BECB.S31601.
J. Pan, C. Jiang, and T. Zhu, “Classification of urine sediment based on convolution neural network,” AIP Conference Proceedings 1955, 040176 pp. 1-5, Apr. 2018. doi.org/10.1063/ 1.5033 840.
A. A. S. Gunawan, D. Brandon, V. D. Puspa, and B. Wiweko, “Development of Urine Hydration System Based on Urine Color and Support Vector Machine,” 3rd International Conference on Computer Science and Computational Intelligence 2018, Procedia Computer Science 135, pp. 481- 489, 2018.
A. A. H.Gadalla, I. M. Friberg, A. Kift-Morgan, J. Zhang, M. Eberl, N. Topley, I. Weeks, S. Cuff, M. Wootton, M. Gal, G. Parekh, P. Davis, C. Gregory, K. Hood, K. Hughes, C. Butler, and N. A. Francis, “Identifcation of clinical and urine biomarkers for uncomplicated urinary tract infection using machine learning algorithms,” Scientific Reports(2019) 9:19694, pp. 1-11, Dec. 2019. doi.org/10.1038/s41598?019-55523-x.
A. Pouliakis, E. Karakitsou, N. Margari, P. Bountris, M. Haritou, J. Panayiotides, D. Koutsouris, and P. Karakitsos, “Artificial Neural Networks as Decision Support Tools in Cytopathology: Past, Present, and Future,” Biomedical Engineering and Computational Biology, 2016:7, pp. 1-18, Jan. 2016. doi:10.4137/BECB.S31601.
J. Pan, C. Jiang, and T. Zhu, “Classification of urine sediment based on convolution neural network,” AIP Conference Proceedings 1955, 040176 pp. 1-5, Apr. 2018. doi.org/10.1063/ 1.5033 840.
A. A. S. Gunawan, D. Brandon, V. D. Puspa, and B. Wiweko, “Development of Urine Hydration System Based on Urine Color and Support Vector Machine,” 3rd International Conference on Computer Science and Computational Intelligence 2018, Procedia Computer Science 135, pp. 481- 489, 2018.
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UCI(KEPA) : I410-ECN-0101-2020-004-001564509