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Can AI guide supplemental breast MRI screening?


In a retrospective study involving over 2,000 women, a team of researchers from Massachusetts General Hospital led by presenter Dr.¬†Kimeya Ghaderi found that risk assessment performed on a deep learning-based model would have led to fewer patients categorized as having intermediate five-year risk or long-term high-risk — without sacrificing on positive predictive values, sensitivity, or specificity.


“A deep learning risk-assessment model can support more effective supplemental breast MRI screening compared to traditional risk assessment models, as measured by the cancer detection rates…



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