A significant trend is the development of large, pre-trained ‘foundation models’ that learn general representations from massive datasets, which can then be adapted (fine-tuned) for specific downstream applications [ 119 ].
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Exploring machine learning strategies for single-cell transcriptomic analysis in wound healing.
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