AI Reveals Diagnostic Biases In Breast Imaging
Conti et al. publish a JMIR Medical Informatics review on March 30, 2026 examining cognitive and system-related sources of diagnostic errors in breast imaging and the role of AI. The paper cites prospective studies showing improved cancer detection and reduced workload from AI-assisted mammography but warns AI can introduce anchoring and automation biases. It recommends targeted training, standardized workflows, and explainable AI to mitigate errors.
Scoring Rationale
Comprehensive, peer-reviewed review with direct clinical recommendations; high scope and relevance for breast imaging practitioners. Novelty is moderate because the paper synthesizes existing prospective studies, but actionable mitigation strategies and JMIR publication credibility boost the score.
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Sources
- Read OriginalViewpoint on the Consequences and Mitigation of Cognitive Bias in the Radiological Interpretation of Breast Cancer Imaging Using Artificial Intelligencemedinform.jmir.org
