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Artificial intelligence–driven elucidation of the mechanistic links between proximal joint strength and tibial loading in Medial Tibial Stress Syndrome runners: implications for precision rehabilitation
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DOI：10.1016/j.apmr.2026.05.023.png)
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Abstract
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This study leveraged machine learning algorithms to observationally elucidate how proximal joint muscle activation patterns—particularly those involving the trunk and hip—are associated with the modulation of tibial loading during running. These findings may provide preliminary theoretical insights into reducing tibial loading during running in individuals with Medial Tibial Stress Syndrome (MTSS) and preventing recurrence.
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