activity
20162019
most citedRetrofitting Concept Vector Representations of Medical Concepts to Improve Estimates of Semantic Similarity and Relatedness

17 citations · 26 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CY20199 cited

Learning to Identify Patients at Risk of Uncontrolled Hypertension Using Electronic Health Records Data

Ramin Mohammadi, Sarthak Jain, Stephen Agboola +3

Hypertension is a major risk factor for stroke, cardiovascular disease, and end-stage renal disease, and its prevalence is expected to rise dramatically. Effective hypertension man…

cs.CL2019

Predicting Annotation Difficulty to Improve Task Routing and Model Performance for Biomedical Information Extraction

Yinfei Yang, Oshin Agarwal, Chris Tar +2

Modern NLP systems require high-quality annotated data. In specialized domains, expert annotations may be prohibitively expensive. An alternative is to rely on crowdsourcing to red…

cs.CL201717 cited

Retrofitting Concept Vector Representations of Medical Concepts to Improve Estimates of Semantic Similarity and Relatedness

Zhiguo Yu, Byron C. Wallace, Todd Johnson +1

Estimation of semantic similarity and relatedness between biomedical concepts has utility for many informatics applications. Automated methods fall into two categories: methods bas…

cs.CL2016

Modelling Context with User Embeddings for Sarcasm Detection in Social Media

Silvio Amir, Byron C. Wallace, Hao Lyu +1

We introduce a deep neural network for automated sarcasm detection. Recent work has emphasized the need for models to capitalize on contextual features, beyond lexical and syntacti…

cs.CL2016

MGNC-CNN: A Simple Approach to Exploiting Multiple Word Embeddings for Sentence Classification

Ye Zhang, Stephen Roller, Byron Wallace

We introduce a novel, simple convolution neural network (CNN) architecture - multi-group norm constraint CNN (MGNC-CNN) that capitalizes on multiple sets of word embeddings for sen…