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The rapid increase in cell biology techniques, combined with high-throughput technologies and improved computing, has yielded complex data that classical methods struggle to analyze. The question arises, can a machine overcome human performance to identify and predict distinct biological scenarios? Here, we review the mechanotransduction of extracellular matrix mechanical cues and how Artificial Intelligence-based methodologies are or can be used to predict cell states based on morphological and genetic signatures.
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Oria et al. (2025) studied this question.
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