Comparison of various deep learning methods (including but not limited to Graph Convolutional Neural Networks, Generative Adversarial Networks, referenced as DESC [1], scDeepCluster [2], scDMFK [3], scziDesk [4], scAIDE [5], scGMAI [6], scCAN [7], and scDCCA [8]) in data feature extraction and clustering performance evaluation on different test datasets (single-cell RNA sequencing data, spatial transcriptomics data, image data). Comparative analysis of the strengths and weaknesses of different methods.
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