Evaluation and improvement of algorithmic fairness for COVID-19 severity classification using Explainable Artificial Intelligence-based bias mitigation

The XAI-driven bias mitigation intervention effectively reduces sex-based disparities in COVID-19 severity prediction without the significant accuracy loss observed in traditional methods. This approach provides a framework for developing fair and accurate clinical decision support systems for older adults, which ensures equitable care in clinical risk stratification and resource allocation.

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Publication Details

Journal
JAMIA Open
Published
2025-12-04
DOI
https://doi.org/10.1093/jamiaopen/ooaf171
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Evaluation and improvement of algorithmic fairness for COVID-19 severity classification using Explainable Artificial Intelligence-based bias mitigation

Samira Abbasgholizadeh Rahimi, Charlene Ronquillo, Shayan Nejadshamsi, Katherine S. McGilton et al.
JAMIA Open
Artificial Intelligence in Healthcare and Education
article

Evaluation and improvement of algorithmic fairness for COVID-19 severity classification using Explainable Artificial Intelligence-based bias mitigation

Samira Abbasgholizadeh Rahimi, Charlene Ronquillo, Shayan Nejadshamsi, Katherine S. McGilton, Charlene H. Chu, Xiaoxiao Li
article en

Abstract

The XAI-driven bias mitigation intervention effectively reduces sex-based disparities in COVID-19 severity prediction without the significant accuracy loss observed in traditional methods. This approach provides a framework for developing fair and accurate clinical decision support systems for older adults, which ensures equitable care in clinical risk stratification and resource allocation.

JAMIA OpenVol. 9(1)
University Health Network (CA), University of British Columbia (CA), University of Toronto (CA), Toronto Rehabilitation Institute (CA), McGill University Health Centre (CA), Jewish General Hospital (CA), Mila - Quebec Artificial Intelligence Institute (CA), McGill University (CA), Okanagan University College (CA)
Openalex Percentile: Top 67%
Artificial Intelligence in Healthcare and Education
DOIOpen Access PDFOpenAlex
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Evaluation and improvement of algorithmic fairness for COVID-19 severity classification using Explainable Artificial Intelligence-based bias mitigation — Samira Abbasgholizadeh Rahimi, Charlene Ronquillo, et al. · JAMIA Open (2025) | TGRS Research Map | TGRS