Search Results for author:
Found 7 papers, 1 papers with code
Three-level Hierarchical Transformer Networks for Long-sequence and Multiple Clinical Documents Classification
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.
Generalized and Transferable Patient Language Representation for Phenotyping with Limited Data
The paradigm of representation learning through transfer learning has the potential to greatly enhance clinical natural language processing.
Deep Representation Learning of Patient Data from Electronic Health Records (EHR): A Systematic Review
We show the importance and feasibility of learning comprehensive representations of patient EHR data through a systematic review.
Extracting Concepts for Precision Oncology from the Biomedical Literature
Finally, we propose additional directions for research for improving extraction performance and utilizing the NLP system in downstream precision oncology applications.
Understanding Spatial Language in Radiology: Representation Framework, Annotation, and Spatial Relation Extraction from Chest X-ray Reports using Deep Learning
We define a representation framework for extracting spatial information from radiology reports (Rad-SpRL).
Enhancing Clinical Concept Extraction with Contextual Embeddings
We explore a battery of embedding methods consisting of traditional word embeddings and contextual embeddings, and compare these on four concept extraction corpora: i2b2 2010, i2b2 2012, SemEval 2014, and SemEval 2015.
Ranked #1 on
Clinical Concept Extraction
on 2010 i2b2/VA
