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
{"title":"用机器学习方法预测五忌丸的疗效","authors":"Haiqing Li, Guozheng Li, William Yang, Ying Chen, Xiaoxin Zhu, Mary Yang","doi":"10.1109/BIBM.2016.7822720","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":345384,"journal":{"name":"2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","volume":"240 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Prediction of the efficacy of Wuji Pills by machine learning methods\",\"authors\":\"Haiqing Li, Guozheng Li, William Yang, Ying Chen, Xiaoxin Zhu, Mary Yang\",\"doi\":\"10.1109/BIBM.2016.7822720\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":345384,\"journal\":{\"name\":\"2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)\",\"volume\":\"240 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BIBM.2016.7822720\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIBM.2016.7822720","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信