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.
Deep Learning Based on Automated Breast V olume Scanner Images for the Diagnosis of Breast Lesions: A Multicenter Diagnostic Study,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
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.