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

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…

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

Extracting drug–drug interactions from literature using a rich feature-based linear kernel approach

Identifying unknown drug interactions is of great benefit in the early detection of adverse drug reactions. Despite existence of several resources for drug–drug interaction (DDI) information, the wealth of such informati…

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 …