Name
Title | ||
|---|---|---|
Precise prediction of multiple anticancer drug efficacy using multi target regression and support vector regression analysis |
Abstract | ||
|---|---|---|
•The enhanced multi target regression and support vector regression was found to be the most effective and accurate method for the selection of anticancer drugs based on tumor features of the patients in a personalized manner.•Increasing the training samples and statistical feature engineering improve the robustness of the model.•EL_MTR is the best to predict multiple anticancer drug efficacies and improve the accuracy of ranking drugs, irrespective of sample size.•ELM_SVR performs better than other MTR models with a large sample size and precise ranking process. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.cmpb.2022.107027 | Computer Methods and Programs in Biomedicine |
Keywords | DocType | Volume |
Oral squamous cell carcinoma,Support vector regression,Precision medicine,Computational models,Multi target drug efficacy prediction | Journal | 224 |
ISSN | Citations | PageRank |
0169-2607 | 0 | 0.34 |
References | Authors | |
13 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| G R Brindha | 1 | 0 | 0.34 |
| B S Rishiikeshwer | 2 | 0 | 0.34 |
| B Santhi | 3 | 0 | 0.34 |
| K Nakendraprasath | 4 | 0 | 0.34 |
| R Manikandan | 5 | 0 | 0.34 |
| Amir Hossein Gandomi | 6 | 1836 | 110.25 |