يعرض 601 - 620 نتائج من 2,767 نتيجة بحث عن '(( significant decrease decrease ) OR ( significance ((a decrease) OR (mean decrease)) ))~', وقت الاستعلام: 0.28s تنقيح النتائج
  1. 601
  2. 602
  3. 603
  4. 604
  5. 605
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  7. 607

    Characteristics of JIA patients. حسب Yasmine Makhlouf (17409866)

    منشور في 2025
    "…Twelve studies published between 2003 and 2018 were analyzed, encompassing 1513 patients with a mean age of 11.4 years. Tumor necrosis factor alpha inhibitors were the predominant biologic agents used (75.8%), with a mean follow-up duration of 2 years post-biologic therapy initiation. …"
  8. 608

    List of excluded articles. حسب Yasmine Makhlouf (17409866)

    منشور في 2025
    "…Twelve studies published between 2003 and 2018 were analyzed, encompassing 1513 patients with a mean age of 11.4 years. Tumor necrosis factor alpha inhibitors were the predominant biologic agents used (75.8%), with a mean follow-up duration of 2 years post-biologic therapy initiation. …"
  9. 609
  10. 610

    Assessment values of machine learning models. حسب Bin Pan (742525)

    منشور في 2025
    "…The prediction results indicate that the StackBoost model excels in predicting aqueous solubility, achieving a coefficient of determination () of 0.90, a root mean square error (RMSE) of 0.29, and a mean absolute error (MAE) of 0.22, significantly outperforming the other comparative models. …"
  11. 611

    List of datasets in AqSolDB. حسب Bin Pan (742525)

    منشور في 2025
    "…The prediction results indicate that the StackBoost model excels in predicting aqueous solubility, achieving a coefficient of determination () of 0.90, a root mean square error (RMSE) of 0.29, and a mean absolute error (MAE) of 0.22, significantly outperforming the other comparative models. …"
  12. 612

    Feature importance derived from SHAP analysis. حسب Bin Pan (742525)

    منشور في 2025
    "…The prediction results indicate that the StackBoost model excels in predicting aqueous solubility, achieving a coefficient of determination () of 0.90, a root mean square error (RMSE) of 0.29, and a mean absolute error (MAE) of 0.22, significantly outperforming the other comparative models. …"
  13. 613
  14. 614
  15. 615
  16. 616
  17. 617
  18. 618
  19. 619
  20. 620