2.2k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of Massachusetts AmherstUS12 papers
- University of Massachusetts LowellUS6 papers
- Amherst CollegeUS4 papers
- Duke UniversityUS4 papers
- Allen Institute for Cell ScienceUS3 papers
- Bedford VA Research CorporationUS3 papers
- Broad InstituteUS3 papers
- Carl Zeiss (Germany)DE3 papers
- Centre National de la Recherche ScientifiqueFR3 papers
- Cornell UniversityUS3 papers
- Delft University of TechnologyNL3 papers
- École Polytechnique Fédérale de LausanneCH3 papers
10 papers · 1 filter
Associations Between Natural Language Processing (NLP) Enriched Social Determinants of Health and Suicide Death among US Veterans
Avijit Mitra, Richeek Pradhan, Rachel D Melamed +8
Importance: Social determinants of health (SDOH) are known to be associated with increased risk of suicidal behaviors, but few studies utilized SDOH from unstructured electronic he…
Automated Identification of Eviction Status from Electronic Health Record Notes
Zonghai Yao, Jack Tsai, Weisong Liu +4
Objective: Evictions are important social and behavioral determinants of health. Evictions are associated with a cascade of negative events that can lead to unemployment, housing i…
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…
MetaMT,a MetaLearning Method Leveraging Multiple Domain Data for Low Resource Machine Translation
Rumeng Li, Xun Wang, Hong Yu
Manipulating training data leads to robust neural models for MT.
Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds
John P. Lalor, Hao Wu, Hong Yu
Incorporating Item Response Theory (IRT) into NLP tasks can provide valuable information about model performance and behavior. Traditionally, IRT models are learned using human res…
Sentence Simplification with Memory-Augmented Neural Networks
Tu Vu, Baotian Hu, Tsendsuren Munkhdalai +1
Sentence simplification aims to simplify the content and structure of complex sentences, and thus make them easier to interpret for human readers, and easier to process for downstr…
Learning to Extract Coherent Summary via Deep Reinforcement Learning
Yuxiang Wu, Baotian Hu
Coherence plays a critical role in producing a high-quality summary from a document. In recent years, neural extractive summarization is becoming increasingly attractive. However,…
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…
Soft Label Memorization-Generalization for Natural Language Inference
John P. Lalor, Hao Wu, Hong Yu
Often when multiple labels are obtained for a training example it is assumed that there is an element of noise that must be accounted for. It has been shown that this disagreement…
Structured prediction models for RNN based sequence labeling in clinical text
Abhyuday Jagannatha, Hong Yu
Sequence labeling is a widely used method for named entity recognition and information extraction from unstructured natural language data. In clinical domain one major application…