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A Multi-Modal Graph-Based Semi-Supervised Pipeline for Predicting Cancer Survival
Despite the wealth of information available in expression profiles of cancer tumors, fulfilling the aforementioned objective remains a big challenge, for the most part, due to the paucity of data samples compared to the high dimension of the expression profiles.
A Semi-Supervised Method for Predicting Cancer Survival Using Incomplete Clinical Data
The results of applying our method to three cancer datasets show the promise of semi-supervised learning for prediction of cancer survival.
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