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largest decrease » larger decrease (Expand Search), marked decrease (Expand Search)
values decrease » values increased (Expand Search)
linear decrease » linear increase (Expand Search)
largest decrease » larger decrease (Expand Search), marked decrease (Expand Search)
values decrease » values increased (Expand Search)
linear decrease » linear increase (Expand Search)
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1521
Noncontinuous data on opioid use.
Published 2025“…Orthopaedic Surgery patients saw a mean 45% reduction in prescription size from 462 MMEs (range: 50–7200 MMEs) to 197 MMEs (range: 25–2400 MMEs) (p < .001), while General Surgery patients experienced a mean 38% reduction from 100 MMEs (range: 25–150 MMEs) to 60 MMEs (range: 25–150 MMEs) (p < .001). …”
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1522
Data Sheet 1_Impact of large-scale oceanic variability on Adriatic fisheries evidenced through the ‘mean temperature of the catch’ approach.docx
Published 2025“…Our results show that after an initial decreasing trend until the late 1980s at a rate of 0.48°C per decade, the MTC subsequently increased at a rate of 0.24°C per decade. …”
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1523
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1524
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1525
The forest plots of the effect of probiotics on the level of IFN-γ by ELISA (A) and RT-PCR (B) methods.
Published 2025“…Overall, probiotics decreased IFN-γ production with Std diff in means between probiotics and control groups was -2.492 with ELISA test (A) and -2.453 with RT-PCR test (B).…”
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1526
Interaction between competition and individual variability.
Published 2025“…<p>The rate at which the lower signal frequency among the two members of the society grows is given by the upper curve, while that for the higher signal is given by the lower curve. When the mean of these two frequencies exceeds , the lower signal frequency increases faster than the higher frequency decreases (shown by the arrows), yielding a net increase for this majority signal.…”
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1527
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1528
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1529
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1530
Features on GMSC dataset used in NATE.
Published 2024“…Logistic regression is widely used in credit scoring due to its robustness, interpretability, and computational efficiency; however, its predictive power decreases when applied to complex or non-linear datasets, resulting in reduced accuracy. …”
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1531
Searching space for hyperparameters in Table 7.
Published 2024“…Logistic regression is widely used in credit scoring due to its robustness, interpretability, and computational efficiency; however, its predictive power decreases when applied to complex or non-linear datasets, resulting in reduced accuracy. …”
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1532
GMSC dataset (IR: Imbalance Ratio).
Published 2024“…Logistic regression is widely used in credit scoring due to its robustness, interpretability, and computational efficiency; however, its predictive power decreases when applied to complex or non-linear datasets, resulting in reduced accuracy. …”
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1533
Under-sampled dataset.
Published 2024“…Logistic regression is widely used in credit scoring due to its robustness, interpretability, and computational efficiency; however, its predictive power decreases when applied to complex or non-linear datasets, resulting in reduced accuracy. …”
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1534
The system architecture of NATE.
Published 2024“…Logistic regression is widely used in credit scoring due to its robustness, interpretability, and computational efficiency; however, its predictive power decreases when applied to complex or non-linear datasets, resulting in reduced accuracy. …”
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1535
Over-sampled dataset.
Published 2024“…Logistic regression is widely used in credit scoring due to its robustness, interpretability, and computational efficiency; however, its predictive power decreases when applied to complex or non-linear datasets, resulting in reduced accuracy. …”
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1536
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1537
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1538
S1 File - Utilization of psychotropic drugs in Serbia from 2006 to 2021: Patterns before and during the COVID-19 pandemic
Published 2025“…<p><b>S1A Fig:</b> Linear regression analysis shows statistically insignificant changes in trends in the consumption of psychotropic drugs in the observed time period. …”
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1539
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1540