Mining the associations between pharmic quality and ingredients of traditional Chinese medicines

Xia Wu, Hui-Jin Wang, Guo-ming Chen, Weiheng Zhu, Shun Long
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Abstract

This paper presents our works to tackle three key problems in modern research of traditional Chinese medicines. Based on a dataset of 100 medicines (each with 60 major ingredients), we evaluate various data mining approaches in order to unveil the underlying associations between these chemical ingredients and the pharmic qualities of the medicines. Based on our experiements, we conclude that these associations do exist and can be effectively unveiled. Various performance enhancement techniques are then evaluated, among which we identify the best classification approach for practice. These unveiled associations between pharmic quality and ingredients of traditional Chinese medicine can help guide future researches in this area, particularly in the development of new medicines.
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挖掘中药成分与药物质量的关系
本文介绍了我们为解决中药现代研究中的三个关键问题所做的工作。基于100种药物(每种药物有60种主要成分)的数据集,我们评估了各种数据挖掘方法,以揭示这些化学成分与药物质量之间的潜在关联。根据我们的实验,我们得出结论,这些关联确实存在,并且可以有效地揭示出来。然后评估了各种性能增强技术,其中我们确定了最佳的分类方法。这些揭示的中药成分与药物质量之间的关系有助于指导这一领域的未来研究,特别是新药的开发。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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