基于多支持向量机的中医鉴别诊断

Jian-jun Yan, Yiqin Wang, Zhaoxia Xu, Guoping Liu, F. L, Rui Guo, Yong Shen, Chunming Xia
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引用次数: 3

摘要

中医鉴别诊断是中医的核心。中医诊断学的客观研究是目前的研究热点。中医的鉴别诊断过程是非常复杂和非线性的。支持向量机(SVM)是一种建立中医诊断模型的新方法。本文建立了基于多支持向量机的诊断模型。比较了高斯核函数和多核函数在支持向量机差分诊断中的应用。提出的基于多支持向量机的模型能较好地处理伴随证候。该模型为中医鉴别诊断提供了一种新的解决方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-SVM based differential diagnostics in TCM
The differential diagnostics of Traditional Chinese Medicine is the kernel of TCM. The objective study of TCM diagnostics is a research hot spot at present. The differential diagnostics process of TCM is very complex and nonlinear. Support Vector Machine (SVM) is a novel method to establish the diagnosis model of TCM. In this paper, the differential diagnostics model is constructed base on multi-SVM. A comparison is made between gaussian and poly kernel functions in SVM for differential diagnostics. The model based on multi-SVM presented can deal with accompanying syndromes better. The model can provide a new way to solve TCM differential diagnostics.
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