Showing 1 - 20 results of 3,456 for search '(( cluster 2 decrease ) OR ( a ((larger decrease) OR (marked decrease)) ))', query time: 0.52s Refine Results
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    Biases in larger populations. by Sander W. Keemink (21253563)

    Published 2025
    “…<p>(<b>A</b>) Maximum absolute bias vs the number of neurons in the population for the Bayesian decoder. …”
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    B2 decreases glycolytic intermediates in cells. by Craig Eyster (392633)

    Published 2025
    “…The box indicates the clustering of decreased downstream glycolytic intermediates in B2-treated cells. …”
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    Study-related adverse events. by Benjamin R. Lewis (22279166)

    Published 2025
    “…We recorded 12 study-related, Grade 1–2 AEs and no serious AEs. In a linear mixed model analysis (LMM), the MBSR + PAP arm evidenced a significantly larger decrease in QIDS-SR-16 score than the MBSR-only arm from baseline to 2-weeks post-intervention (between-groups effect = 4.6, 95% CI [1.51, 7.70]; <i>p</i> = 0.008). …”
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    Study flow chart. by Benjamin R. Lewis (22279166)

    Published 2025
    “…We recorded 12 study-related, Grade 1–2 AEs and no serious AEs. In a linear mixed model analysis (LMM), the MBSR + PAP arm evidenced a significantly larger decrease in QIDS-SR-16 score than the MBSR-only arm from baseline to 2-weeks post-intervention (between-groups effect = 4.6, 95% CI [1.51, 7.70]; <i>p</i> = 0.008). …”
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    Study CONSORT diagram. by Benjamin R. Lewis (22279166)

    Published 2025
    “…We recorded 12 study-related, Grade 1–2 AEs and no serious AEs. In a linear mixed model analysis (LMM), the MBSR + PAP arm evidenced a significantly larger decrease in QIDS-SR-16 score than the MBSR-only arm from baseline to 2-weeks post-intervention (between-groups effect = 4.6, 95% CI [1.51, 7.70]; <i>p</i> = 0.008). …”
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    K-means++ clustering algorithm. by Zhen Zhao (159931)

    Published 2025
    “…Additionally, considering the imbalanced in population spatial distribution, we used the K-means ++ clustering algorithm to cluster the optimal feature subset, and we used the bootstrap sampling method to extract the same amount of data from each cluster and fuse it with the training subset to build an improved random forest model. …”