6 citations · 16 across the 8 of their papers we have counts for
10 papers · 1 filter
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…
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…
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…
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…
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…