most citedDeep Learning Models in Detection of Dietary Supplement Adverse Event Signals from Twitter

1 citations · 1 across the 2 of their papers we have counts for

collaborators

3 papers

cs.IR2021

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…

cs.CL2021★ 1 cited

Deep Learning Models in Detection of Dietary Supplement Adverse Event Signals from Twitter

Yefeng Wang, Yunpeng Zhao, Jiang Bian +1

Objective: The objective of this study is to develop a deep learning pipeline to detect signals on dietary supplement-related adverse events (DS AEs) from Twitter. Material and Met…

cs.CL2020

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…