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A Generative Self-Supervised Framework using Functional Connectivity in fMRI Data
Deep neural networks trained on Functional Connectivity (FC) networks extracted from functional Magnetic Resonance Imaging (fMRI) data have gained popularity due to the increasing availability of data and advances in model architectures, including Graph Neural Network (GNN).
Slot-Mixup with Subsampling: A Simple Regularization for WSI Classification
Due to the lack of patch-level labels, multiple instance learning (MIL) is a common practice for training a WSI classifier.
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