Automated detection of stigmatizing language in Electronic Health Records (EHRs) using a multi-stage transfer learning approach

This framework offers a statistically validated, high-performing framework for detecting stigmatizing language in EHRs, supporting responsible AI and promoting equity in clinical care.

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Publication Details

Journal
Journal of the American Medical Informatics Association
Published
2025-11-09
DOI
https://doi.org/10.1093/jamia/ocaf193
Citations
2
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
4.96
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article

Automated detection of stigmatizing language in Electronic Health Records (EHRs) using a multi-stage transfer learning approach

Vivek K. Singh, Charles Senteio, Aminur Rahman, Liyang Xue
2 citations
Journal of the American Medical Informatics Association
Machine Learning in Healthcare
4.96
article

Automated detection of stigmatizing language in Electronic Health Records (EHRs) using a multi-stage transfer learning approach

Vivek K. Singh, Charles Senteio, Aminur Rahman, Liyang Xue
article en
2 citations

Abstract

This framework offers a statistically validated, high-performing framework for detecting stigmatizing language in EHRs, supporting responsible AI and promoting equity in clinical care.

Journal of the American Medical Informatics AssociationVol. 33(2)
Rutgers, The State University of New Jersey (US)
Openalex Percentile: Top 4%
Machine Learning in Healthcare
4.96
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