32 citations · 117 across the 14 of their papers we have counts for
17 papers
Vision Meets Definitions: Unsupervised Visual Word Sense Disambiguation Incorporating Gloss Information
Sunjae Kwon, Rishabh Garodia, Minhwa Lee +2
Visual Word Sense Disambiguation (VWSD) is a task to find the image that most accurately depicts the correct sense of the target word for the given context. Previously, image-text…
Context Variance Evaluation of Pretrained Language Models for Prompt-based Biomedical Knowledge Probing
Zonghai Yao, Yi Cao, Zhichao Yang +1
Pretrained language models (PLMs) have motivated research on what kinds of knowledge these models learn. Fill-in-the-blanks problem (e.g., cloze tests) is a natural approach for ga…
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…
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…
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…
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,…
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…
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…
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…
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…
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…
Ranking medical jargon in electronic health record notes by adapted distant supervision
Jinying Chen, Abhyuday N. Jagannatha, Samah J. Jarad +1
Objective: Allowing patients to access their own electronic health record (EHR) notes through online patient portals has the potential to improve patient-centered care. However, me…
Learning to Rank Scientific Documents from the Crowd
Jesse M Lingeman, Hong Yu
Finding related published articles is an important task in any science, but with the explosion of new work in the biomedical domain it has become especially challenging. Most exist…
Bidirectional Recurrent Neural Networks for Medical Event Detection in Electronic Health Records
Abhyuday Jagannatha, Hong Yu
Sequence labeling for extraction of medical events and their attributes from unstructured text in Electronic Health Record (EHR) notes is a key step towards semantic understanding…
Neural Tree Indexers for Text Understanding
Tsendsuren Munkhdalai, Hong Yu
Recurrent neural networks (RNNs) process input text sequentially and model the conditional transition between word tokens. In contrast, the advantages of recursive networks include…
Neural Semantic Encoders
Tsendsuren Munkhdalai, Hong Yu
We present a memory augmented neural network for natural language understanding: Neural Semantic Encoders. NSE is equipped with a novel memory update rule and has a variable sized…
Learning for Biomedical Information Extraction: Methodological Review of Recent Advances
Feifan Liu, Jinying Chen, Abhyuday Jagannatha +1
Biomedical information extraction (BioIE) is important to many applications, including clinical decision support, integrative biology, and pharmacovigilance, and therefore it has b…