activity
20192021
most citedCross-lingual Data Transformation and Combination for Text Classification

2 citations · 6 across the 4 of their papers we have counts for

collaborators

6 papers

cs.LG2021

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…

cs.LG20212 cited

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…

physics.med-ph20202 cited

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…

cs.CL2019

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…

cs.IR2019

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…

cs.IR20192 cited

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…