Automated Annotation of Pain Chronicity in Patients With Back Pain by Using Electronic Health Records: Retrospective Study

Our study indicates that pain chronicity from EHR data could be used to study more topics on larger datasets in the future without the need for manual annotation and that using NLP tools to automate prediction is feasible.

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Publication Details

Journal
JMIR Formative Research
Published
2026-03-05
DOI
https://doi.org/10.2196/63198
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
0.00
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article

Automated Annotation of Pain Chronicity in Patients With Back Pain by Using Electronic Health Records: Retrospective Study

J. D. Bailey, Simran Ajay Kanal, Thomas Peterson, Jeffrey Lotz
JMIR Formative Research
Machine Learning in Healthcare
article

Automated Annotation of Pain Chronicity in Patients With Back Pain by Using Electronic Health Records: Retrospective Study

J. D. Bailey, Simran Ajay Kanal, Thomas Peterson, Jeffrey Lotz
article en

Abstract

Our study indicates that pain chronicity from EHR data could be used to study more topics on larger datasets in the future without the need for manual annotation and that using NLP tools to automate prediction is feasible.

JMIR Formative ResearchVol. 10
University of California, San Francisco (US)
Quality Education
Openalex Percentile: Top 37%
Machine Learning in Healthcare
DOIOpen Access PDFOpenAlex
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