Why Clinical AI Will Keep Failing Women Until We Validate Across Hormonal States
Year: 2026
Type: article
Abstract: We identify the absence of hormonal-dynamic validation as a structural bottleneck in clinical AI fairness and propose a concrete protocol to address it. The protocol centers on a tiered multi-modal data stack anchored by nocturnal basal heart rate variability, serum hormone assays, and STRAW+10 menopausal staging, applied within a longitudinal mixed-effects framework that treats race as a moderator of hormonal transition slope. We introduce the Endocrine Volatility Score (EVS), the coefficient of variation of a model’s true positive rate across hormonal states as a quantitative transparency metric for a public Hormonal Fidelity Index.
Author: Rytsareva, Inna
Language: English
Subfield: Safety Research
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W7158662483
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