3 citations · 3 across the 3 of their papers we have counts for
5 papers
Discovering novel drug-supplement interactions using a dietary supplements knowledge graph generated from the biomedical literature
Dalton Schutte, Jake Vasilakes, Anu Bompelli +7
OBJECTIVE: Leverage existing biomedical NLP tools and DS domain terminology to produce a novel and comprehensive knowledge graph containing dietary supplement (DS) information for…
UIUC_BioNLP at SemEval-2021 Task 11: A Cascade of Neural Models for Structuring Scholarly NLP Contributions
Haoyang Liu, M. Janina Sarol, Halil Kilicoglu
We propose a cascade of neural models that performs sentence classification, phrase recognition, and triple extraction to automatically structure the scholarly contributions of NLP…
Drug Repurposing for COVID-19 via Knowledge Graph Completion
Rui Zhang, Dimitar Hristovski, Dalton Schutte +3
Objective: To discover candidate drugs to repurpose for COVID-19 using literature-derived knowledge and knowledge graph completion methods. Methods: We propose a novel, integrative…
Attention-Gated Graph Convolutions for Extracting Drug Interaction Information from Drug Labels
Tung Tran, Ramakanth Kavuluru, Halil Kilicoglu
Preventable adverse events as a result of medical errors present a growing concern in the healthcare system. As drug-drug interactions (DDIs) may lead to preventable adverse events…
A Multi-Task Learning Framework for Extracting Drugs and Their Interactions from Drug Labels
Tung Tran, Ramakanth Kavuluru, Halil Kilicoglu
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 a…