يعرض 1 - 20 نتائج من 4,807 نتيجة بحث عن '(( shows ((mae decrease) OR (mean decrease)) ) OR ( a ((larger decrease) OR (marked decrease)) ))', وقت الاستعلام: 0.58s تنقيح النتائج
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    Cinacalcet administered early in the inactive phase markedly decrease parathyroid Ki-67 index. حسب Søren Egstrand (10906087)

    منشور في 2025
    "…All groups were compared by Kruskal Wallis test with <i>post hoc</i> test after Dunn with Bonferroni adjustment showing significant decreased Ki-67 labeling index of <i>Cina1</i> compared to <i>Cina2</i> (p = 0.006) and the untreated CKD groups (p = 0.0001 and p = 0.0002, respectively). …"
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    The introduction of mutualisms into assembled communities increases their connectance and complexity while decreasing their richness. حسب Gui Araujo (22170819)

    منشور في 2025
    "…Parameter values: interaction strengths were drawn from a half-normal distribution of zero mean and a standard deviation of 0.2, and strength for consumers was made no larger than the strength for resources. …"
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    Comparison of Mean Absolute Error (MAE) in Millimeters as a Function of Kernel Size. حسب Liu Liu (512237)

    منشور في 2025
    "…Both models show a decrease in MAE as the kernel size increases up to approximately 200 pixels. …"
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    Evogliptin attenuates the phenotypic switch of VSMCs during CER treatment by decreasing the osteogenesis-associated genes <i>in-vitro.</i> حسب Razia Rashid Rahil (22772495)

    منشور في 2025
    "…<p>(A) Representative images showed calcium deposition (red). (B, C) Summarized bar graph showed EVO significantly decreased calcium deposition and calcium content in CER treated P<sub>i</sub>-induced VSMCs. …"
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    The MAE value of the model under raw data. حسب Xiangjuan Liu (618000)

    منشور في 2025
    "…Subsequently, STL decomposition decoupled the series into trend, seasonal, and residual components for component-specific modeling, achieving a 22.6% reduction in average MAE compared to raw data modeling. Further integration of Spearman correlation analysis and PCA dimensionality reduction created multidimensional feature sets, revealing substantial accuracy improvements: The BiLSTM model achieved an 83.6% cumulative MAE reduction from 1.65 (raw data) to 0.27 (STL-PCA), while traditional models like Prophet showed an 82.2% MAE decrease after feature engineering optimization. …"
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