Showing 1 - 20 results of 44,451 for search '(( significant ((point decrease) OR (small decrease)) ) OR ( significant all increase ))', query time: 0.95s Refine Results
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    Perioperative factors associated with differences in adjusted hospitalization costs; all displayed factors are significantly associated with increased or decreased adjusted costs. by Saad Mallick (17283479)

    Published 2024
    “…<p>Perioperative factors associated with differences in adjusted hospitalization costs; all displayed factors are significantly associated with increased or decreased adjusted costs.…”
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    Summary map of all contacts with statistically significant SVM classifications. by Alexander P. Rockhill (6053618)

    Published 2024
    “…Yellow reflects high classification accuracy, while dark blue represents less robust classification accuracy. Time-frequency points with no significant classification value are white.…”
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    Response of small airway tissues infected with EV-D94 and decreasing doses of EV-D68. by Ines Cordeiro Filipe (5849144)

    Published 2022
    “…<p>Tissues were infected with 1E7 RNA copies of EV-D94 (equivalent to 2,46E4 TCID50) and 1E7 RNA copies of EV-D68 (3,3E5 TCID50) as well as decreasing doses of the latter. A and B: Viral loads were quantified by RT-PCR from apical wash samples collected at the indicated time points (A) or from tissues lysed at 2dpi (B). …”
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    Change in average relative abundance of significantly different ASVs within distinct phyla classifications at all three time points for the three different treatments. by Charlotte H. Wang (8805353)

    Published 2020
    “…</b> For the control treatment, the change in average relative abundance of significantly different bacteria taxa in their relative phyla classifications generally decreased throughout consecutive time points. …”
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    All-variable XGBoost model on the <i>significant illness</i> binary using the all-owner dataset. by Richard Barrett-Jolley (739341)

    Published 2024
    “…<p>(a) Receiver operating characteristic curve of a prediction model containing all variables (owner, animal and healthcare). This shows the increasing true positive and false positive rates, with decrease of the threshold probability for prediction of <i>significant illness</i>. …”
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