Opioid consumption data. by Wali U. Pirzada (22278071)

“…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). …”

Prescription data. by Wali U. Pirzada (22278071)

“…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). …”

Refill rate by surgical specialty. by Wali U. Pirzada (22278071)

“…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). …”

Noncontinuous data on opioid use. by Wali U. Pirzada (22278071)

“…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). …”

Data Sheet 1_Impact of large-scale oceanic variability on Adriatic fisheries evidenced through the ‘mean temperature of the catch’ approach.docx by Elvis Kamberi (22759586)

“…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. …”

The forest plots of the effect of probiotics on the level of TNF-α by ELISA (A) and RT-PCR (B) methods. by Zahra Zangeneh (11772967)

The forest plots of the effect of probiotics on the level of IL-10 by ELISA (A) and RT-PCR (B) methods. by Zahra Zangeneh (11772967)

The forest plots of the effect of probiotics on the level of IFN-γ by ELISA (A) and RT-PCR (B) methods. by Zahra Zangeneh (11772967)

“…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).…”

Interaction between competition and individual variability. by Richard A. Blythe (10912355)

“…<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.…”

Levels of antioxidant enzymes (A) Catalase, (B) Superoxide dismutase, (C) peroxidase. by Hammad Ismail (4227988)

I.p. injection of LPS induces inflammation in the brain A. by Fionä Caratis (12759506)

Local and global interpretability of NATE. by Seongil Han (20490232)

Features on GMSC dataset used in NATE. by Seongil Han (20490232)

“…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. …”

Searching space for hyperparameters in Table 7. by Seongil Han (20490232)

“…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. …”

GMSC dataset (IR: Imbalance Ratio). by Seongil Han (20490232)

“…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. …”

Under-sampled dataset. by Seongil Han (20490232)

“…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. …”

The system architecture of NATE. by Seongil Han (20490232)

“…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. …”

Over-sampled dataset. by Seongil Han (20490232)

“…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. …”

Performance enhancements of classification models using the undersampling method (NearMiss). by Seongil Han (20490232)

Performance enhancements of classification models using the oversampling method (SMOTE). by Seongil Han (20490232)