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Omar Mohammed

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#large language models Open access Aug 2026

Competence Is Not Protection: Prompt-Channel Demographic Bias in Pathology Vision-Language Models, and the Geometry That Predicts It

Part IV of a series on equity and reliability in medical imaging AI. Part III of this series showed that naming a demographic group in the text prompt of a medical vision–language model changes its diagnosis on a fixed chest radiograph, that the perturbation is exactly rank one in the standard positive/negative pair re...

Omar Mohammed · 0 citations
#large language models Open access Aug 2026

The Prompt Is a Confounder: A Counterfactual Audit of Demographic Bias in the Text Channel of Medical Vision-Language Models

Parts I and II of this series audited and attempted to remediate subgroup disparities in chest radiograph(CXR) classifi ers, and Part II declared an explicit limitation: multimodal systems combining imageswith clinical text were out of scope, because “text-derived features may carry demographic informationmore directly...

Omar Mohammed · 0 citations

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