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  Kernelized information-theoretic metric learning for cancer diagnosis using high-dimensional molecular profiling data
Xiong F., Kam M., Hrebien L., Wang B., Qi Y.  ACM Transactions on Knowledge Discovery from Data 10(4): Article No. 38, 2016. Type: Article

The molecular gene expressions of tumor and blood samples are useful for detecting cancers. But the design of algorithms for diagnosing cancer using high-dimensional heterogeneous signatures of gene expression data is difficult. How should the hig...
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Sep 9 2016  

   
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