activity
20192021
most citedDeep Learning Approaches for Extracting Adverse Events and Indications of Dietary Supplements from Clinical Text

24 citations · 31 across the 7 of their papers we have counts for

collaborators

7 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.CL2021

A Conversational Agent System for Dietary Supplements Use

Esha Singh, Anu Bompelli, Ruyuan Wan +3

Dietary supplements (DS) have been widely used by consumers, but the information around the efficacy and safety of DS is disparate or incomplete, thus creating barriers for consume…

cs.CL2021★ 4 cited

Extracting Lifestyle Factors for Alzheimer's Disease from Clinical Notes Using Deep Learning with Weak Supervision

Zitao Shen, Yoonkwon Yi, Anusha Bompelli +3

Since no effective therapies exist for Alzheimer's disease (AD), prevention has become more critical through lifestyle factor changes and interventions. Analyzing electronic health…

cs.IR2020★ 24 cited

Deep Learning Approaches for Extracting Adverse Events and Indications of Dietary Supplements from Clinical Text

Yadan Fan, Sicheng Zhou, Yifan Li +1

The objective of our work is to demonstrate the feasibility of utilizing deep learning models to extract safety signals related to the use of dietary supplements (DS) in clinical t…

cs.SI2019★ 1 cited

Mining Twitter to Assess the Determinants of Health Behavior towards Human Papillomavirus Vaccination in the United States

Hansi Zhang, Christopher Wheldon, Adam G. Dunn +6

Objectives To test the feasibility of using Twitter data to assess determinants of consumers' health behavior towards Human papillomavirus (HPV) vaccination informed by the Integra…

cs.CY2019★ 1 cited

Analyzing Social Media Data to Understand Consumers' Information Needs on Dietary Supplements

Rubina F. Rizvi, Yefeng Wang, Thao Nguyen +4

Despite the high consumption of dietary supplements (DS), there are not many reliable, relevant, and comprehensive online resources that could satisfy information seekers. The purp…