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To develop and evaluate a radiomic phenotyping and multi-lesion aggregation scheme to derive patient-level biomarkers for identifying progressive disease and predicting time-to-progression (TTP) in diffuse large B-cell lymphoma (...

To mitigate the loss of spatial information inherent to DVH-based and coarse categorical descriptors used for breast cancer–related lymphedema prediction, we present a multi-modal cross-attention predictive model with self-attent...

Accurate survival prediction following radiation therapy for glioma remains challenging due to heterogeneous tumor biology and treatment response. This study proposes a multimodal framework integrating deep radiomic features from...