基于神经网络的中药黄芩药效评价方法研究

Abstract

Abstract:

How to impersonally and effectively assess the pharmacological effects of traditional Chinese medicine (TCM) is one of the difficulties confronting the modern research of TCM. This paper establishes a neural network model for the assessment of pharmacological effects of traditional Chinese medicine Huang Qin. We train this model with massive data and adjust its model parameters. We therefore construct a union effect assessment system for the traditional Chinese medicine Huang Qin. Test results show the advances and reliability of this method.

Key words: quality assessment of a traditional Chinese medicine, chromatographic fingerprint and pharmacological effect correlation mode, neural network, fingerprint

CLC Number:

R284.1

HOU En-Guang, LI Shu-Bin, LI Ke, DING Xiao-Yan, LV Ling, LIU Qing, ZHAO Bo-Nian, XU Zong-Yuan. Neural network based assessment of pharmacological effects of traditional Chinese medicine[J].J4, 2011, 24(1): 72-76.

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Open Access This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0), which permits third parties to freely share (i.e., copy and redistribute the material in any medium or format) and adapt (i.e., remix, transform, or build upon the material) the articles published in this journal, provided that appropriate credit is given, a link to the license is provided, and any changes made are indicated. The material may not be used for commercial purposes. For details of the CC BY-NC 4.0 license, please visit: https://creativecommons.org/licenses/by-nc/4.0

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Neural network based assessment of pharmacological effects of traditional Chinese medicine

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