用机器学习方法预测五忌丸的疗效

Haiqing Li, Guozheng Li, William Yang, Ying Chen, Xiaoxin Zhu, Mary Yang
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引用次数: 1

摘要

疗效预测是中医不可分割的一部分。我们首先分析指标与疗效的相关性,选择最大血药浓度(max blood drug concentration, Cmax)作为反映药物疗效的指标。然后应用线性回归(LR)、支持向量回归(SVR)和人工神经网络(ann)对五极丸的疗效进行预测。留一方法的结果表明,对于标签Cmax, SVR的性能优于其他方法,是一种很好的方法。为了找到无忌丸各成分之间的关系,采用了几种可视化方法来处理这一问题。预测网络服务器可在http://data.jindengtai.cn/#/case/drug上公开使用。
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Prediction of the efficacy of Wuji Pills by machine learning methods
Efficacy prediction is an inseparable part of TCM. We firstly analyze the correlation between indicators and efficacy, and max blood-drug concentration(Cmax) is chosen as the target to reflect the efficacy of drugs. Then we apply linear regression(LR), support vector regression(SVR) as well as artificial neural networks(ANNs) to predict the efficacy of Wuji pills. The results of the leave-one-out method show that SVR performs better than other methods for label Cmax, and appears to be a good method for this task. In order to find the relationship between each component of Wuji Pills, several visualization methods are adopted to deal with this problem. The web server of prediction is available at http://data.jindengtai.cn/#/case/drug for public usage.
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