Deep learning predicts HER2 status in invasive breast cancer from multimodal ultrasound and MRI.

Both applications highlight the need for larger validation cohorts to address statistical uncertainties—particularly regarding the borderline significance of the multimodal model—and to clarify its potential benefits in reducing diagnostic errors, patient anxiety, and healthcare costs through improved specificity.

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