SurvConvMixer: robust and interpretable cancer survival prediction based on ConvMixer using pathway-level gene expression images
Shuo Wang,
Yuanning Liu,
Hao Zhang
et al.
Abstract:Cancer is one of the leading causes of deaths worldwide. Survival analysis and prediction of cancer patients is of great significance for their precision medicine. The robustness and interpretability of the survival prediction models are important, where robustness tells whether a model has learned the knowledge, and interpretability means if a model can show human what it has learned. In this paper, we propose a robust and interpretable model SurvConvMixer, which uses pathways customized gene expression image… Show more
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