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14th International Conference on Computer and Knowledge Engineering
Virus-Antiviral Prediction Using Machine and Deep Learning Methods
Authors :
Shayan Majidifar
1
Fatemeh Nasiri
2
Mohsen Hooshmand
3
1- Institute for Advanced Studies in Basic Sciences (IASBS)
2- Institute for Advanced Studies in Basic Sciences (IASBS)
3- Assistant Professor
Keywords :
Drug repurposing،Machine learning،Virus،Antiviral،Deep learning،Dataset
Abstract :
Prediction of new virus-antiviral associations is significant in the treatment of virus diseases. This work proposes a prediction framework for finding new associations among the virus diseases and approved antivirals. To do this, we have generated a new virus-antiviral dataset. Additionally, we propose a prediction framework using random forest, SVM, XGBoost, and a deep learning model. The results are promising and XGBoost outperforms all other methods in the prediction of virus-antiviral associations.
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