Article

Automated Extraction of Stroke Severity from Unstructured Electronic Health Records using Natural Language Processing

2024-03-11

Abstract excerpt

<h4>BACKGROUND</h4> Multi-center electronic health records (EHR) can support quality improvement initiatives and comparative effectiveness research in stroke care. However, limitations of EHR-based research include challenges in abstracting key clinical variables from non-structured data at scale. This is further compounded by missing data. Here we develop a natural language processing (NLP) model that automatical...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: c292caac-73e5-5a75-8ed1-ebde78074f1b
DOI: 10.1101/2024.03.08.24304011

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Automated Extraction of Stroke Severity from Unstructured Electronic Health Records using Natural Language ProcessingDOI 10.1101/2024.03.08.24304011Read

Development and Application of Natural Language Processing on Unstructured Data in Hypertension: A Scoping ReviewSemantic proximity Read

Prognosis of stroke subtypes in whole population health systems data: a matched cohort studySemantic proximity Read

Large Language Models in Stroke Management: A Review of the LiteratureSemantic proximity Read

Natural Language Processing for assessing multimorbidity: A systematic reviewSemantic proximity Read

Scalable information extraction from free text electronic health records using large language modelsSemantic proximity Read

SPELL: A Scalable NLP Method Using Regular Expressions and Large Language Models for Clinical Information ExtractionSemantic proximity Read

Extracting Carotid Stenosis Severity from Clinical Notes Using Natural Language Processing: Development, Validation, and Application in a Nationwide Veteran CohortSemantic proximity Read

Longitudinal information extraction from clinical notes in rare diseases: an efficient approach with small language modelsSemantic proximity Read

Comparative analysis, applications, and interpretation of electronic health record-based stroke phenotyping methodsSemantic proximity Read

Comparison of Large Language Models Versus Traditional Information Extraction Methods for Real World Evidence of Patient Symptomatology in Acute and Post-Acute Sequelae of SARS-CoV-2Semantic proximity Read