activity
20192024
most citedExtraction and Analysis of Clinically Important Follow-up Recommendations in a Large Radiology Dataset

3 citations · 7 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL20243 cited

CACER: Clinical Concept Annotations for Cancer Events and Relations

Yujuan Fu, Giridhar Kaushik Ramachandran, Ahmad Halwani +5

Clinical notes contain unstructured representations of patient histories, including the relationships between medical problems and prescription drugs. To investigate the relationsh…

cs.CL20211 cited

Jointly Learning Clinical Entities and Relations with Contextual Language Models and Explicit Context

Paul Barry, Sam Henry, Meliha Yetisgen +2

We hypothesize that explicit integration of contextual information into an Multi-task Learning framework would emphasize the significance of context for boosting performance in joi…

cs.CL2021

Transferability of Neural Network Clinical De-identification Systems

Kahyun Lee, Nicholas J. Dobbins, Bridget McInnes +2

Objective: Neural network de-identification studies have focused on individual datasets. These studies assume the availability of a sufficient amount of human-annotated data to tra…

cs.CL2020

Annotating Social Determinants of Health Using Active Learning, and Characterizing Determinants Using Neural Event Extraction

Kevin Lybarger, Mari Ostendorf, Meliha Yetisgen

Social determinants of health (SDOH) affect health outcomes, and knowledge of SDOH can inform clinical decision-making. Automatically extracting SDOH information from clinical text…

cs.CL20193 cited

Extraction and Analysis of Clinically Important Follow-up Recommendations in a Large Radiology Dataset

Wilson Lau, Thomas H Payne, Ozlem Uzuner +1

Communication of follow-up recommendations when abnormalities are identified on imaging studies is prone to error. In this paper, we present a natural language processing approach…