AI Triage Could Cut Mammography Radiologist Workload by Over Three-Quarters

AI triaging of low-risk screening mammograms could remove >75% of cases from radiologist review, freeing capacity for high-risk exams, per a new Radiology: Artificial Intelligence study — corroborating a growing body of similar findings.

• Published in Radiology: Artificial Intelligence; specific study design, sample size, and performance metrics (sensitivity/specificity, AUC) are not reported in the available source snippet.
• The approach focuses on identifying low-risk exams that can safely bypass additional radiologist review, theoretically concentrating expert attention on higher-yield cases.
• Key limitation cannot be fully assessed from the snippet; external validation status, false-negative rate for triaged cases, and generalizability across screening populations are critical unknowns not addressed in the source.

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