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The study of SVM-based recognition of particles in urine sediment / 中国医疗器械杂志
Article in Chinese | WPRIM (Western Pacific) | ID: wpr-309564
Responsible library: WPRO
ABSTRACT
This article used support vector machine (SVM) algorithm to recognize the particles in urine sediment in this paper. After feature extraction, cross-validation method and the contour chart of the accuracy were implemented to select the kernel function and the parameters of SVM, and according to the characteristics of SVM classifier and sample data, Multi-SVMs with two-level-classifier was successfully designed and A classification matrix was eventually obtained. The evaluation by using clinical data and comparative results with the artificial neural network have demonstrated that the proposed algorithm gets better results.
Subject(s)
Full text: Available Database: WPRIM (Western Pacific) Main subject: Particle Size / Urine / Algorithms / Pattern Recognition, Automated / Artificial Intelligence / Chemistry / Methods Limits: Humans Language: Chinese Journal: Chinese Journal of Medical Instrumentation Year: 2008 Document type: Article
Full text: Available Database: WPRIM (Western Pacific) Main subject: Particle Size / Urine / Algorithms / Pattern Recognition, Automated / Artificial Intelligence / Chemistry / Methods Limits: Humans Language: Chinese Journal: Chinese Journal of Medical Instrumentation Year: 2008 Document type: Article
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