AttentionDDI: Siamese attention-based deep learning method for drug–drug interaction predictions

AttentionDDI: Siamese attention-based deep learning method for drug–drug interaction predictions

Background: Drug–drug interactions (DDIs) refer to processes triggered by the administration of two or more drugs leading to side effects beyond those observed when drugs are administered by themselves. Due to the massive number of possible drug pairs, it is nearly impossible to experimentally test...

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Bibliographic Details
Main Authors: Allam, A. (Author), Krauthammer, M. (Author), Perez Gonzalez, N.A (Author), Schwarz, K. (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
adverse drug reaction
Attention
Attention mechanisms
Benchmark datasets
Benchmarking
Deep learning
Deep Learning
drug
drug interaction
Drug interactions
Drug Interactions
Drug–drug interactions
Drug-Related Side Effects and Adverse Reactions
Forecasting
Gene expression
Gene expression profiles
human
Humans
Interaction prediction
Learning systems
Multi-modal neural networks
NAtural language processing
Natural language processing systems
Neural networks
Neural Networks, Computer
Pharmaceutical Preparations
Prediction
Prediction performance
Predictive analytics
Side effects
Similarity measure
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Internet

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