A new multimodal fusion model using image, text, and clinical encoders with Transformer fusion reaches 77.64% accuracy on a pathology-confirmed 910-patient breast ultrasound dataset for distinguishing fibroadenoma from phyllodes tumors.
Classification of asymmetry in mammography via the DenseNet convolutional neural network,
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Multimodal Fusion for Fine-Grained Classification of Breast Fibroadenoma and Phyllodes Tumors
A new multimodal fusion model using image, text, and clinical encoders with Transformer fusion reaches 77.64% accuracy on a pathology-confirmed 910-patient breast ultrasound dataset for distinguishing fibroadenoma from phyllodes tumors.