338 citations · 757 across the 20 of their papers we have counts for
10 papers · 1 filter
Evaluation of AI Chatbots for Patient-Specific EHR Questions
Alaleh Hamidi, Kirk Roberts
This paper investigates the use of artificial intelligence chatbots for patient-specific question answering (QA) from clinical notes using several large language model (LLM) based…
Eye-SpatialNet: Spatial Information Extraction from Ophthalmology Notes
Surabhi Datta, Tasneem Kaochar, Hio Cheng Lam +5
We introduce an annotated corpus of 600 ophthalmology notes labeled with detailed spatial and contextual information of ophthalmic entities. We extend our previously proposed frame…
Toward a Neural Semantic Parsing System for EHR Question Answering
Sarvesh Soni, Kirk Roberts
Clinical semantic parsing (SP) is an important step toward identifying the exact information need (as a machine-understandable logical form) from a natural language query aimed at…
Deep learning-based NLP Data Pipeline for EHR Scanned Document Information Extraction
Enshuo Hsu, Ioannis Malagaris, Yong-Fang Kuo +2
Scanned documents in electronic health records (EHR) have been a challenge for decades, and are expected to stay in the foreseeable future. Current approaches for processing often…
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…
Leveraging Spatial Information in Radiology Reports for Ischemic Stroke Phenotyping
Surabhi Datta, Shekhar Khanpara, Roy F. Riascos +1
Classifying fine-grained ischemic stroke phenotypes relies on identifying important clinical information. Radiology reports provide relevant information with context to determine s…
RadLex Normalization in Radiology Reports
Surabhi Datta, Jordan Godfrey-Stovall, Kirk Roberts
Radiology reports have been widely used for extraction of various clinically significant information about patients' imaging studies. However, limited research has focused on stand…
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…