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Deceptive Bias Measurement in Deep Learning: Assessing Shortcut Reliance in TCGA Cancer Models
2025-12-15
pathology
Title + abstract only
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Bias in machine learning is a persistent challenge because it can create unfair outcomes, limit generalization, and reduce trust in real-world applications. A key source of this problem is shortcut learning, where models exploit signals linked to sensitive attributes, such as data source or collection site, instead of relying on task, relevant features. To tackle this, we propose the Deceptive Signal metric, a novel quantitative measure designed to assess the extent of a models reliance on hidde...
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