A multimodal framework fusing CNV, clinical data, and both image- and graph-based histopathology representations improves PAM50 subtyping accuracy to 78.13% and macro-AUC to 0.9153 on TCGA-BRCA.
Quantitative proteomics study of breast cancer cell lines isolated from a single patient: discovery of timm17a as a marker for breast cancer
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Scalable and Loosely-Coupled Multimodal Deep Learning for Breast Cancer Subtyping
A multimodal framework fusing CNV, clinical data, and both image- and graph-based histopathology representations improves PAM50 subtyping accuracy to 78.13% and macro-AUC to 0.9153 on TCGA-BRCA.