activity
20182021
most citedComparisons of Graph Neural Networks on Cancer Classification Leveraging a Joint of Phenotypic and Genetic Features

2 citations · 2 across the 3 of their papers we have counts for

collaborators

9 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…

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.DB2019

Towards Semantic Big Graph Analytics for Cross-Domain Knowledge Discovery

Feichen Shen

In recent years, the size of big linked data has grown rapidly and this number is still rising. Big linked data and knowledge bases come from different domains such as life science…

cs.IR2018

MedSTS: A Resource for Clinical Semantic Textual Similarity

Yanshan Wang, Naveed Afzal, Sunyang Fu +4

The wide adoption of electronic health records (EHRs) has enabled a wide range of applications leveraging EHR data. However, the meaningful use of EHR data largely depends on our a…

cs.IR2018

A Deep Representation Empowered Distant Supervision Paradigm for Clinical Information Extraction

Yanshan Wang, Sunghwan Sohn, Sijia Liu +5

Objective: To automatically create large labeled training datasets and reduce the efforts of feature engineering for training accurate machine learning models for clinical informat…