Name
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. |
Year | Venue | Keywords |
|---|---|---|
2016 | 2016 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM) | SVR, ANNs, efficacy prediction, leave-one-out, drug metabolism |
Field | DocType | ISSN |
Data mining,Computer science,Support vector machine,Pill,Correlation,Artificial intelligence,Artificial neural network,Cmax,Machine learning,Linear regression | Conference | 2156-1125 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Haiqing Li | 1 | 0 | 0.34 |
| Guo-Zheng Li | 2 | 368 | 42.62 |
| Ying Chen | 3 | 0 | 0.34 |
| Xiaoxin Zhu | 4 | 0 | 0.34 |
| William Yang | 5 | 36 | 5.82 |
| Mary Qu Yang | 6 | 933 | 191.35 |