Drug–drug interaction (DDI) is an important part of drug development and
pharmacovigilance. At the same time, DDI is an important factor in treatment planning …

Drug–drug interaction (DDI) is an important safety issue during clinical treatment, where the
mechanism of action of drugs may interfere with each other thereby causing adverse effects …

The identification of Drug-Drug Interactions (DDIs) is crucial for optimizing patient treatment
and avoiding adverse reactions. With the rapid growth of biomedical literature, manual …

Advances in deep learning models have revolutionized the study of biomolecule systems
and their mechanisms. Graph representation learning, in particular, is important for …

Drug-drug interaction (DDI) extraction has seen growing usage of deep models, but their
effectiveness has been restrained by limited domain-labeled data, a weak representation of …

Predicting drug–drug interactions (DDIs) is crucial for understanding and preventing
adverse drug reactions (ADRs). However, most existing methods inadequately explore the …

The concurrent use of multiple medications to treat one or more diseases is prevalent.
Identifying N-ary drug combinations from biomedical texts aids in uncovering significant …

Motivation Drug repurposing (DR) is an imminent approach for identifying novel therapeutic
indications for the available drugs and discovering novel drugs for previously untreatable …

Featured Application With this contribution, we aim to aid the drug development process as
well as the identification of possible adverse drug events due to simultaneous drug use …

Introduction Drug-drug interaction (DDI) may lead to adverse reactions in patients, thus it is
important to extract such knowledge from biomedical texts. However, previously proposed …