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advances in machine learning and data-intensive approaches facilitate the search for better or even global minima via evolutionary computations or reinforcement learning. Objectives. The main scientific
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within a coherent computational model is currently challenging, due to the typical large dimension and complexity of biomedical data, and the relative low sample size available in typical clinical studies
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, ranging from biological to clinical features. The integration of such heterogeneous information within a coherent computational model is currently challenging, due to the typical large dimension and
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evolutionary conservation across vertebrates in terms of muscle pattern and innervation modes (1–3). The coexistence of both vulnerable and resilient muscles within the same organism provides compelling in vivo