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Multi-feature concatenation and multi-classifier stacking: an interpretable and generalizable machine learning method for MDD discrimination with rsfMRI
In addition, the generalizability of MFMC is validated by the good performance when the training and testing subjects are from independent sites.
CoarSAS2hvec: Heterogeneous Information Network Embedding with Balanced Network Sampling
Hence, the traditional loss function applied to samples by CoarSAS can also yield improved results.
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