338 citations · 604 across the 6 of their papers we have counts for
6 papers
Three-level Hierarchical Transformer Networks for Long-sequence and Multiple Clinical Documents Classification
Yuqi Si, Kirk Roberts
We present a Three-level Hierarchical Transformer Network (3-level-HTN) for modeling long-term dependencies across clinical notes for the purpose of patient-level prediction. The n…
Generalized and Transferable Patient Language Representation for Phenotyping with Limited Data
Yuqi Si, Elmer V Bernstam, Kirk Roberts
The paradigm of representation learning through transfer learning has the potential to greatly enhance clinical natural language processing. In this work, we propose a multi-task p…
Deep Representation Learning of Patient Data from Electronic Health Records (EHR): A Systematic Review
Yuqi Si, Jingcheng Du, Zhao Li +5
Patient representation learning refers to learning a dense mathematical representation of a patient that encodes meaningful information from Electronic Health Records (EHRs). This…
Extracting Concepts for Precision Oncology from the Biomedical Literature
Nicholas Greenspan, Yuqi Si, Kirk Roberts
This paper describes an initial dataset and automatic natural language processing (NLP) method for extracting concepts related to precision oncology from biomedical research articl…
Understanding Spatial Language in Radiology: Representation Framework, Annotation, and Spatial Relation Extraction from Chest X-ray Reports using Deep Learning
Surabhi Datta, Yuqi Si, Laritza Rodriguez +3
We define a representation framework for extracting spatial information from radiology reports (Rad-SpRL). We annotated a total of 2000 chest X-ray reports with 4 spatial roles cor…
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…