An unsupervised clustering framework on athlete biomarkers identifies coherent profiles distinguishing mechanical damage from metabolic stress while preserving homeostatic states.
Lim- itations of separating athletes into high or low-risk groups based on a cut-off: A clinical commentary
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An unsupervised decision-support framework for multivariate biomarker analysis in athlete monitoring
An unsupervised clustering framework on athlete biomarkers identifies coherent profiles distinguishing mechanical damage from metabolic stress while preserving homeostatic states.