Web: http://arxiv.org/abs/2201.10353

Jan. 26, 2022, 2:11 a.m. | Kaiwen Tan, Weixian Huang, Xiaofeng Liu, Jinlong Hu, Shoubin Dong

cs.LG updates on arXiv.org arxiv.org

Morphological attributes from histopathological images and molecular profiles
from genomic data are important information to drive diagnosis, prognosis, and
therapy of cancers. By integrating these heterogeneous but complementary data,
many multi-modal methods are proposed to study the complex mechanisms of
cancers, and most of them achieve comparable or better results from previous
single-modal methods. However, these multi-modal methods are restricted to a
single task (e.g., survival analysis or grade classification), and thus neglect
the correlation between different tasks. In this …

arxiv cancer correlation framework learning prediction

More from arxiv.org / cs.LG updates on arXiv.org

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