b'Hong Yu'

research

∙ 08/07/2023

PaniniQA: Enhancing Patient Education Through Interactive Question Answering

Patient portal allows discharged patients to access their personalized d...

0 Pengshan Cai, et al. ∙

research

∙ 07/26/2023

Mental-LLM: Leveraging Large Language Models for Mental Health Prediction via Online Text Data

Advances in large language models (LLMs) have empowered a variety of app...

0 Xuhai Xu, et al. ∙

research

∙ 07/23/2023

Early Prediction of Alzheimers Disease Leveraging Symptom Occurrences from Longitudinal Electronic Health Records of US Military Veterans

Early prediction of Alzheimer's disease (AD) is crucial for timely inter...

0 Rumeng Li, et al. ∙

research

∙ 07/05/2023

ODD: A Benchmark Dataset for the NLP-based Opioid Related Aberrant Behavior Detection

Opioid related aberrant behaviors (ORAB) present novel risk factors for ...

0 Sunjae Kwon, et al. ∙

research

∙ 06/29/2023

UMASS_BioNLP at MEDIQA-Chat 2023: Can LLMs generate high-quality synthetic note-oriented doctor-patient conversations?

This paper presents UMASS_BioNLP team participation in the MEDIQA-Chat 2...

0 Junda Wang, et al. ∙

research

∙ 06/10/2023

Referring to Screen Texts with Voice Assistants

Voice assistants help users make phone calls, send messages, create even...

0 Shruti Bhargava, et al. ∙

research

∙ 05/20/2023

Revisiting the Architectures like Pointer Networks to Efficiently Improve the Next Word Distribution, Summarization Factuality, and Beyond

Is the output softmax layer, which is adopted by most language models (L...

0 Haw-Shiuan Chang, et al. ∙

research

∙ 05/02/2023

Vision Meets Definitions: Unsupervised Visual Word Sense Disambiguation Incorporating Gloss Information

Visual Word Sense Disambiguation (VWSD) is a task to find the image that...

0 Sunjae Kwon, et al. ∙

research

∙ 12/22/2022

Enhancing the prediction of disease outcomes using electronic health records and pretrained deep learning models

Question: Can an encoder-decoder architecture pretrained on a large data...

0 Zhichao Yang, et al. ∙

research

∙ 12/11/2022

Associations Between Natural Language Processing (NLP) Enriched Social Determinants of Health and Suicide Death among US Veterans

Importance: Social determinants of health (SDOH) are known to be associa...

0 Avijit Mitra, et al. ∙

research

∙ 12/06/2022

Automated Identification of Eviction Status from Electronic Health Record Notes

Objective: Evictions are involved in a cascade of negative events that c...

0 Zonghai Yao, et al. ∙

research

∙ 11/26/2022

An Automatic SOAP Classification System Using Weakly Supervision And Transfer Learning

In this paper, we introduce a comprehensive framework for developing a m...

0 Sunjae Kwon, et al. ∙

research

∙ 11/24/2022

Multi-label Few-shot ICD Coding as Autoregressive Generation with Prompt

Automatic International Classification of Diseases (ICD) coding aims to ...

0 Zhichao Yang, et al. ∙

research

∙ 11/18/2022

Context Variance Evaluation of Pretrained Language Models for Prompt-based Biomedical Knowledge Probing

Pretrained language models (PLMs) have motivated research on what kinds ...

0 Zonghai Yao, et al. ∙

research

∙ 10/12/2022

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

This paper proposes a new natural language processing (NLP) application ...

0 Sunjae Kwon, et al. ∙

research

∙ 10/07/2022

Knowledge Injected Prompt Based Fine-tuning for Multi-label Few-shot ICD Coding

Automatic International Classification of Diseases (ICD) coding aims to ...

0 Zhichao Yang, et al. ∙

research

∙ 08/26/2022

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

Language Models (LMs) have performed well on biomedical natural language...

0 Zonghai Yao, et al. ∙

research

∙ 07/26/2022

Advanced Conditional Variational Autoencoders (A-CVAE): Towards interpreting open-domain conversation generation via disentangling latent feature representation

Currently end-to-end deep learning based open-domain dialogue systems re...

0 Ye Wang, et al. ∙

research

∙ 05/29/2022

Learning as Conversation: Dialogue Systems Reinforced for Information Acquisition

We propose novel AI-empowered chat bots for learning as conversation whe...

0 Pengshan Cai, et al. ∙

research

∙ 05/12/2022

ScAN: Suicide Attempt and Ideation Events Dataset

Suicide is an important public health concern and one of the leading cau...

0 Bhanu Pratap Singh Rawat, et al. ∙

research

∙ 04/18/2022

Caption Feature Space Regularization for Audio Captioning

Audio captioning aims at describing the content of audio clips with huma...

0 Yiming Zhang, et al. ∙

research

∙ 06/01/2021

Improving Formality Style Transfer with Context-Aware Rule Injection

Models pre-trained on large-scale regular text corpora often do not work...

0 Zonghai Yao, et al. ∙

research

∙ 05/20/2021

CREAD: Combined Resolution of Ellipses and Anaphora in Dialogues

Anaphora and ellipses are two common phenomena in dialogues. Without res...

0 Bo-Hsiang Tseng, et al. ∙

research

∙ 04/16/2021

Membership Inference Attack Susceptibility of Clinical Language Models

Deep Neural Network (DNN) models have been shown to have high empirical ...

0 Abhyuday Jagannatha, et al. ∙

research

∙ 04/15/2021

A Dual-Questioning Attention Network for Emotion-Cause Pair Extraction with Context Awareness

Emotion-cause pair extraction (ECPE), an emerging task in sentiment anal...

0 Qixuan Sun, et al. ∙

research

∙ 12/14/2020

A prognostic dynamic model applicable to infectious diseases providing easily visualized guides – A case study of COVID-19 in the UK

A reasonable prediction of infectious diseases transmission process unde...

0 Yuxuan Zhang, et al. ∙

research

∙ 10/30/2020

Dynamic Data Selection for Curriculum Learning via Ability Estimation

Curriculum learning methods typically rely on heuristics to estimate the...

0 John P. Lalor, et al. ∙

research

∙ 10/24/2020

Conversational Semantic Parsing for Dialog State Tracking

We consider a new perspective on dialog state tracking (DST), the task o...

0 Jianpeng Cheng, et al. ∙

research

∙ 04/16/2020

Neural Data-to-Text Generation with Dynamic Content Planning

Neural data-to-text generation models have achieved significant advancem...

0 Kai Chen, et al. ∙

research

∙ 04/09/2020

Calibrating Structured Output Predictors for Natural Language Processing

We address the problem of calibrating prediction confidence for output e...

0 Abhyuday Jagannatha, et al. ∙

research

∙ 04/05/2020

Improved Pretraining for Domain-specific Contextual Embedding Models

We investigate methods to mitigate catastrophic forgetting during domain...

0 Subendhu Rongali, et al. ∙

research

∙ 12/11/2019

MetaMT,a MetaLearning Method Leveraging Multiple Domain Data for Low Resource Machine Translation

Manipulating training data leads to robust neural models for MT....

0 Rumeng Li, et al. ∙

research

∙ 11/25/2019

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

Automated ICD coding, which assigns the International Classification of ...

0 Fei Li, et al. ∙

research

∙ 10/09/2019

Large-scale Gastric Cancer Screening and Localization Using Multi-task Deep Neural Network

Gastric cancer is one of the most common cancers, which ranks third amon...

31 Hong Yu, et al. ∙

research

∙ 08/31/2019

Generating Classical Chinese Poems from Vernacular Chinese

Classical Chinese poetry is a jewel in the treasure house of Chinese cul...

5 Zhichao Yang, et al. ∙

research

∙ 08/29/2019

Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds

Incorporating Item Response Theory (IRT) into NLP tasks can provide valu...

0 John P. Lalor, et al. ∙

research

∙ 11/29/2018

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

Hypoglycemia is common and potentially dangerous among those treated for...

10 Yonghao Jin, et al. ∙

research

∙ 09/18/2018

Language Identification with Deep Bottleneck Features

In this paper we proposed an end-to-end short utterances speech language...

0 Zhanyu Ma, et al. ∙

research

∙ 08/02/2018

Deep Neural Network for Analysis of DNA Methylation Data

Many researches demonstrated that the DNA methylation, which occurs in t...

0 Hong Yu, et al. ∙

research

∙ 08/02/2018

Histogram Transform-based Speaker Identification

A novel text-independent speaker identification (SI) method is proposed....

0 Zhanyu Ma, et al. ∙

research

∙ 04/20/2018

Sentence Simplification with Memory-Augmented Neural Networks

Sentence simplification aims to simplify the content and structure of co...

0 Tu Vu, et al. ∙

research

∙ 03/02/2017

Meta Networks

Neural networks have been successfully applied in applications with a la...

0 Tsendsuren Munkhdalai, et al. ∙

research

∙ 03/01/2017

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

Background: Electronic health record (EHR) notes contain abundant medica...

0 Jinying Chen, et al. ∙

research

∙ 02/27/2017

CIFT: Crowd-Informed Fine-Tuning to Improve Machine Learning Ability

Item Response Theory (IRT) allows for measuring ability of Machine Learn...

0 John P. Lalor, et al. ∙

research

∙ 02/15/2017

An Analysis of Ability in Deep Neural Networks

Deep neural networks (DNNs) have made significant progress in a number o...

0 John P. Lalor, et al. ∙

research

∙ 11/14/2016

Ranking medical jargon in electronic health record notes by adapted distant supervision

Objective: Allowing patients to access their own electronic health recor...

0 Jinying Chen, et al. ∙

research

∙ 11/04/2016

Learning to Rank Scientific Documents from the Crowd

Finding related published articles is an important task in any science, ...

0 Jesse M Lingeman, et al. ∙

research

∙ 10/20/2016

Reasoning with Memory Augmented Neural Networks for Language Comprehension

Hypothesis testing is an important cognitive process that supports human...

0 Tsendsuren Munkhdalai, et al. ∙

research

∙ 08/01/2016

Structured prediction models for RNN based sequence labeling in clinical text

Sequence labeling is a widely used method for named entity recognition a...

0 Abhyuday Jagannatha, et al. ∙

research

∙ 07/15/2016

Neural Tree Indexers for Text Understanding

Recurrent neural networks (RNNs) process input text sequentially and mod...

0 Tsendsuren Munkhdalai, et al. ∙

Hong Yu

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