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Adding MRI data to histopathology and gene expression modestly improves glioma survival prediction, but only when combined effectively in a trimodal deep learning model.
Multimodal deep learning models for cancer prognosis may not be synergizing information across modalities as much as we think; better performance seems to come from simply adding complementary signals.
