NIL\_UCM: Extracting Drug-Drug interactions from text through combination of sequence and tree kernels

SCAI: Extracting drug-drug interactions using a rich feature vector

A Multi-Task Learning Framework for Extracting Drugs and Their Interactions from Drug Labels

Preventable adverse drug reactions as a result of medical errors present a growing concern in modern medicine. As drug-drug interactions (DDIs) may cause adverse reactions, being able to extracting DDIs from drug labels …

R-BERT-CNN: Drug-target interactions extraction from biomedical literature

In this research, we present our work participation for the DrugProt task of BioCreative VII challenge. Drug-target interactions (DTIs) are critical for drug discovery and repurposing, which are often manually extracted …

Emerging Drug Interaction Prediction Enabled by Flow-based Graph Neural Network with Biomedical Network

Accurately predicting drug-drug interactions (DDI) for emerging drugs, which offer possibilities for treating and alleviating diseases, with computational methods can improve patient care and contribute to efficient drug…

Predicting Rich Drug-Drug Interactions via Biomedical Knowledge Graphs and Text Jointly Embedding

Minimizing adverse reactions caused by drug-drug interactions has always been a momentous research topic in clinical pharmacology. Detecting all possible interactions through clinical studies before a drug is released to…