AI Model May Help Decipher Malignant, Benign Breast Lesions on MRI

Model matches deep-learning accuracy and helps physicians reclassify benign breast lesions.

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An interpretable AI model may match the diagnostic accuracy of standard deep-learning methods for breast lesion classification.
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The study evaluated a concept bottleneck model using data from 1,695 lesions across five hospitals from 2016 to 2025.
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The CBM achieved an AUC of 0.92 in the test set and maintained high performance with an AUC of 0.93 in external validation.
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Radiologist accuracy improved significantly with CBM assistance, increasing from 71% to 91% and reducing interpretation time.
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The model demonstrated clinical utility by aiding in the correct downgrading of 22% of suspicious benign lesions.

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