Improved prediction of drug-drug interactions using ensemble deep neural networks
Nowadays, combining multiple drugs is the optimal therapy to decelerate the pathologic process, which contains various underlying adverse effects due to drug-drug interactions (DDIs). Artificial intelligence (AI) has the potential to evaluate the interaction, pharmacodynamics, and possible side effe...
Saved in:
Main Authors: | Thanh Hoa Vo (Author), Ngan Thi Kim Nguyen (Author), Nguyen Quoc Khanh Le (Author) |
---|---|
Format: | Book |
Published: |
Elsevier,
2023-02-01T00:00:00Z.
|
Subjects: | |
Online Access: | Connect to this object online. |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Ensemble Deep Neural Network for Automatic Classification of EEG Independent Components
by: Fabio Lopes, et al.
Published: (2022) -
A Novel Deep Neural Network Technique for Drug-Target Interaction
by: Jackson G. de Souza, et al.
Published: (2022) -
Comparison of Target Features for Predicting Drug-Target Interactions by Deep Neural Network Based on Large-Scale Drug-Induced Transcriptome Data
by: Hanbi Lee, et al.
Published: (2019) -
Predicting drug response of tumors from integrated genomic profiles by deep neural networks
by: Yu-Chiao Chiu, et al.
Published: (2019) -
Correction to: Predicting drug response of tumors from integrated genomic profiles by deep neural networks
by: Yu-Chiao Chiu, et al.
Published: (2019)