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20182021
most citedClinical Concept Extraction: a Methodology Review

186 citations · 271 across the 10 of their papers we have counts for

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Showing cs.IRShow all

6 papers · 1 filter

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★ 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…