186 citations · 261 across the 10 of their papers we have counts for
10 papers
Explainable Diagnosis Prediction through Neuro-Symbolic Integration
Qiuhao Lu, Rui Li, Elham Sagheb +5
Diagnosis prediction is a critical task in healthcare, where timely and accurate identification of medical conditions can significantly impact patient outcomes. Traditional machine…
Large Language Models Struggle in Token-Level Clinical Named Entity Recognition
Qiuhao Lu, Rui Li, Andrew Wen +3
Large Language Models (LLMs) have revolutionized various sectors, including healthcare where they are employed in diverse applications. Their utility is particularly significant in…
An Open Natural Language Processing Development Framework for EHR-based Clinical Research: A case demonstration using the National COVID Cohort Collaborative (N3C)
Sijia Liu, Andrew Wen, Liwei Wang +28
While we pay attention to the latest advances in clinical natural language processing (NLP), we can notice some resistance in the clinical and translational research community to a…
Leveraging a Joint of Phenotypic and Genetic Features on Cancer Patient Subgrouping
David Oniani, Chen Wang, Yiqing Zhao +3
Cancer is responsible for millions of deaths worldwide every year. Although significant progress has been achieved in cancer medicine, many issues remain to be addressed for improv…
Comparisons of Graph Neural Networks on Cancer Classification Leveraging a Joint of Phenotypic and Genetic Features
David Oniani, Chen Wang, Yiqing Zhao +3
Cancer is responsible for millions of deaths worldwide every year. Although significant progress hasbeen achieved in cancer medicine, many issues remain to be addressed for improvi…
Real-World Data Analysis of Implantable Cardioverter Defibrillator (ICD) in Patients with Hypertrophic Cardiomyopathy (HCM)
Sungrim Moon, Andrew Wen, Christopher G. Scott +7
Background: One of the common causes of sudden cardiac death (SCD) in young people is hypertrophic cardiomyopathy (HCM) and the primary prevention of SCD is with an implantable car…
Adapting and evaluating a deep learning language model for clinical why-question answering
Andrew Wen, Mohamed Y. Elwazir, Sungrim Moon +1
Objectives: To adapt and evaluate a deep learning language model for answering why-questions based on patient-specific clinical text. Materials and Methods: Bidirectional encoder r…
Clinical Concept Extraction: a Methodology Review
Sunyang Fu, David Chen, Huan He +10
Background Concept extraction, a subdomain of natural language processing (NLP) with a focus on extracting concepts of interest, has been adopted to computationally extract clinica…
Cross-lingual Data Transformation and Combination for Text Classification
Jun Jiang, Shumao Pang, Xia Zhao +4
Text classification is a fundamental task for text data mining. In order to train a generalizable model, a large volume of text must be collected. To address data insufficiency, cr…
CREATE: Cohort Retrieval Enhanced by Analysis of Text from Electronic Health Records using OMOP Common Data Model
Sijia Liu, Yanshan Wang, Andrew Wen +6
Background: Widespread adoption of electronic health records (EHRs) has enabled secondary use of EHR data for clinical research and healthcare delivery. Natural language processing…