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

11 papers

cs.IR20229 cited

Extracting Biomedical Factual Knowledge Using Pretrained Language Model and Electronic Health Record Context

Zonghai Yao, Yi Cao, Zhichao Yang +2

Language Models (LMs) have performed well on biomedical natural language processing applications. In this study, we conducted some experiments to use prompt methods to extract know…

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…

q-bio.OT20201 cited

Ontology-based annotation and analysis of COVID-19 phenotypes

Yang Wang, Fengwei Zhang, Hong Yu +2

The epidemic of COVID-19 has caused an unpredictable and devastated disaster to the public health in different territories around the world. Common phenotypes include fever, cough,…

q-bio.OT20205 cited

Ontology-based systematic classification and analysis of coronaviruses, hosts, and host-coronavirus interactions towards deep understanding of COVID-19

Hong Yu, Li Li, Hsin-hui Huang +17

Given the existing COVID-19 pandemic worldwide, it is critical to systematically study the interactions between hosts and coronaviruses including SARS-Cov, MERS-Cov, and SARS-CoV-2…

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…