Modeling Dense Multimodal Interactions Between Biological Pathways and Histology for Survival Prediction. (arXiv:2304.06819v1 [cs.CV])

Integrating whole-slide images (WSIs) and bulk transcriptomics for predicting
patient survival can improve our understanding of patient prognosis. However,
this multimodal task is particularly challenging due to the different nature of
these data: WSIs represent a very high-dimensional spatial description of a
tumor, while bulk transcriptomics represent a global description of gene
expression levels within that tumor. In this context, our work aims to address
two key challenges: (1) how can we tokenize transcriptomics in a semantically
meaningful and interpretable …

arxiv bulk challenges context data gene global images interactions modeling multimodal nature patient prediction survival understanding work