338 citations · 453 across the 6 of their papers we have counts for
6 papers
Identifying and Extracting Rare Disease Phenotypes with Large Language Models
Cathy Shyr, Yan Hu, Paul A. Harris +1
Rare diseases (RDs) are collectively common and affect 300 million people worldwide. Accurate phenotyping is critical for informing diagnosis and treatment, but RD phenotypes are o…
An Empirical Study of UMLS Concept Extraction from Clinical Notes using Boolean Combination Ensembles
Greg M. Silverman, Raymond L. Finzel, Michael V. Heinz +10
Our objective in this study is to investigate the behavior of Boolean operators on combining annotation output from multiple Natural Language Processing (NLP) systems across multip…
Discovering novel drug-supplement interactions using a dietary supplements knowledge graph generated from the biomedical literature
Dalton Schutte, Jake Vasilakes, Anu Bompelli +7
OBJECTIVE: Leverage existing biomedical NLP tools and DS domain terminology to produce a novel and comprehensive knowledge graph containing dietary supplement (DS) information for…
Robustly Pre-trained Neural Model for Direct Temporal Relation Extraction
Hong Guan, Jianfu Li, Hua Xu +1
Background: Identifying relationships between clinical events and temporal expressions is a key challenge in meaningfully analyzing clinical text for use in advanced AI application…
BERT-based Ranking for Biomedical Entity Normalization
Zongcheng Ji, Qiang Wei, Hua Xu
Developing high-performance entity normalization algorithms that can alleviate the term variation problem is of great interest to the biomedical community. Although deep learning-b…
Enhancing Clinical Concept Extraction with Contextual Embeddings
Yuqi Si, Jingqi Wang, Hua Xu +1
Neural network-based representations ("embeddings") have dramatically advanced natural language processing (NLP) tasks, including clinical NLP tasks such as concept extraction. Rec…