activity
20152021
most citedClinical Concept Extraction: a Methodology Review

186 citations · 288 across the 17 of their papers we have counts for

collaborators

17 papers

cs.CL2021★ 1 cited

An Empirical Study of UMLS Concept Extraction from Clinical Notes using Boolean Combination Ensembles

Greg M. Silverman, Raymond L. Finzel, Michael V. Heinz +10

Our objective in this study is to investigate the behavior of Boolean operators on combining annotation output from multiple Natural Language Processing (NLP) systems across multip…

cs.IR2021★ 2 cited

CancerBERT: a BERT model for Extracting Breast Cancer Phenotypes from Electronic Health Records

Sicheng Zhou, Liwei Wang, Nan Wang +2

Accurate extraction of breast cancer patients' phenotypes is important for clinical decision support and clinical research. Current models do not take full advantage of cancer doma…

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.LG2021★ 2 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…

eess.IV2020★ 3 cited

Digital pathology-based study of cell- and tissue-level morphologic features in serous borderline ovarian tumor and high-grade serous ovarian cancer

Jun Jiang, Burak Tekin, Ruifeng Guo +3

Serous borderline ovarian tumor (SBOT) and high-grade serous ovarian cancer (HGSOC) are two distinct subtypes of epithelial ovarian tumors, with markedly different biologic backgro…

physics.med-ph2020★ 2 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.IR2019★ 186 cited

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.IR2019

How Good is Artificial Intelligence at Automatically Answering Consumer Questions Related to Alzheimer's Disease?

Krishna B. Soundararajan, Sunyang Fu, Luke A. Carlson +4

Alzheimer's Disease (AD) is the most common type of dementia, comprising 60-80% of cases. There were an estimated 5.8 million Americans living with Alzheimer's dementia in 2019, an…

cs.IR2019★ 2 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…

stat.AP2019★ 6 cited

Unsupervised Machine Learning for the Discovery of Latent Disease Clusters and Patient Subgroups Using Electronic Health Records

Yanshan Wang, Yiqing Zhao, Terry M. Therneau +6

Machine learning has become ubiquitous and a key technology on mining electronic health records (EHRs) for facilitating clinical research and practice. Unsupervised machine learnin…

cs.IR2019★ 25 cited

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…

cs.IR2018★ 3 cited

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★ 4 cited

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…

cs.IR2018★ 22 cited

Detection of Surgical Site Infection Utilizing Automated Feature Generation in Clinical Notes

Feichen Shen, David W Larson, James M. Naessens +3

Postsurgical complications (PSCs) are known as a deviation from the normal postsurgical course and categorized by severity and treatment requirements. Surgical site infection (SSI)…

cs.IR2018★ 28 cited

A Comparison of Word Embeddings for the Biomedical Natural Language Processing

Yanshan Wang, Sijia Liu, Naveed Afzal +5

Word embeddings have been widely used in biomedical Natural Language Processing (NLP) applications as they provide vector representations of words capturing the semantic properties…

cs.IR2016

MatLM: a Matrix Formulation for Probabilistic Language Models

Yanshan Wang, Hongfang Liu

Probabilistic language models are widely used in Information Retrieval (IR) to rank documents by the probability that they generate the query. However, the implementation of the pr…

cs.IR2015★ 2 cited

Generalized Ensemble Model for Document Ranking in Information Retrieval

Yanshan Wang, In-Chan Choi, Hongfang Liu

A generalized ensemble model (gEnM) for document ranking is proposed in this paper. The gEnM linearly combines basis document retrieval models and tries to retrieve relevant docume…