activity
20162022
most citedLearning for Biomedical Information Extraction: Methodological Review of Recent Advances

32 citations · 107 across the 8 of their papers we have counts for

collaborators
Showing cs.CLShow all

8 papers · 1 filter

cs.CL2022

MedJEx: A Medical Jargon Extraction Model with Wiki's Hyperlink Span and Contextualized Masked Language Model Score

Sunjae Kwon, Zonghai Yao, Harmon S. Jordan +3

This paper proposes a new natural language processing (NLP) application for identifying medical jargon terms potentially difficult for patients to comprehend from electronic health…

cs.CL202121 cited

Membership Inference Attack Susceptibility of Clinical Language Models

Abhyuday Jagannatha, Bhanu Pratap Singh Rawat, Hong Yu

Deep Neural Network (DNN) models have been shown to have high empirical privacy leakages. Clinical language models (CLMs) trained on clinical data have been used to improve perform…

cs.CL20195 cited

ICD Coding from Clinical Text Using Multi-Filter Residual Convolutional Neural Network

Fei Li, Hong Yu

Automated ICD coding, which assigns the International Classification of Disease codes to patient visits, has attracted much research attention since it can save time and labor for…

cs.CL2019

Generating Classical Chinese Poems from Vernacular Chinese

Zhichao Yang, Pengshan Cai, Yansong Feng +4

Classical Chinese poetry is a jewel in the treasure house of Chinese culture. Previous poem generation models only allow users to employ keywords to interfere the meaning of genera…

cs.CL2018

HYPE: A High Performing NLP System for Automatically Detecting Hypoglycemia Events from Electronic Health Record Notes

Yonghao Jin, Fei Li, Hong Yu

Hypoglycemia is common and potentially dangerous among those treated for diabetes. Electronic health records (EHRs) are important resources for hypoglycemia surveillance. In this s…

cs.CL201721 cited

Unsupervised Ensemble Ranking of Terms in Electronic Health Record Notes Based on Their Importance to Patients

Jinying Chen, Hong Yu

Background: Electronic health record (EHR) notes contain abundant medical jargon that can be difficult for patients to comprehend. One way to help patients is to reduce information…