KAISEN: Reproducible Subgroup Fairness Auditing for Clinical Risk Models
Clinical risk models routinely achieve strong aggregate performance while producing materially different error rates across patient subgroups. Audit pipelines have been proposed to catch this, but their components are rarely stress-tested, so it is unclear which parts of an audit can be trusted and under what conditions. We present KAISEN, a five-phase audit pipeline covering subgroup stratification, disparity measurement, mechanism diagnostics, post-hoc mitigation, and drift monitoring, evaluat
Record details
Published: 30 July 2026
Source: arXiv cs.LG
Category: Research
Topics: Bias & fairness · Healthcare · Transparency
Retrieved: 31 July 2026
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ethics.ai (30 July 2026), “KAISEN: Reproducible Subgroup Fairness Auditing for Clinical Risk Models,” evidence record 15250, https://ethics.ai/record/15250 (originally published by arXiv cs.LG).
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