Computer Science > Machine Learning
[Submitted on 31 Oct 2024 (v1), last revised 6 Nov 2024 (this version, v2)]
Title:Monitoring fairness in machine learning models that predict patient mortality in the ICU
View PDF HTML (experimental)Abstract:This work proposes a fairness monitoring approach for machine learning models that predict patient mortality in the ICU. We investigate how well models perform for patient groups with different race, sex and medical diagnoses. We investigate Documentation bias in clinical measurement, showing how fairness analysis provides a more detailed and insightful comparison of model performance than traditional accuracy metrics alone.
Submission history
From: Tempest Van Schaik [view email][v1] Thu, 31 Oct 2024 20:17:12 UTC (11 KB)
[v2] Wed, 6 Nov 2024 20:32:55 UTC (11 KB)
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