A fully convolutional data description (FCDD) model for identifying anomalies on breast MRI demonstrated an 84 percent AUC for detection tasks in a balanced cohort with a 20 percent malignancy prevalence and a 72 percent AUC for detection tasks in an imbalanced group with a 1.85 percent cancer prevalence.

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