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RadioPathomics: Multimodal Learning in Non-Small Cell Lung Cancer for Adaptive Radiotherapy. (arXiv:2204.12423v1 [cs.LG])
cs.LG updates on arXiv.org arxiv.org
The current cancer treatment practice collects multimodal data, such as
radiology images, histopathology slides, genomics and clinical data. The
importance of these data sources taken individually has fostered the recent
raise of radiomics and pathomics, i.e. the extraction of quantitative features
from radiology and histopathology images routinely collected to predict
clinical outcomes or to guide clinical decisions using artificial intelligence
algorithms. Nevertheless, how to combine them into a single multimodal
framework is still an open issue. In this work we …
arxiv cancer learning lung cancer multimodal multimodal learning small