Immune disease-associated biomarker values are commonly more variable in affected compared to unaffected patient populations, which limits a biomarker’s informative range. Here, the authors formalise a computational solution that splits datasets into informative and uninformative subsets to improve biomarker discovery and performance of multivariate predictive models.
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【저자키워드】 Prognostic markers, Statistical methods, Translational immunology,
【저자키워드】 Prognostic markers, Statistical methods, Translational immunology,