The ROC curves and AUC values of the diagnostic model. by Zhe Wu (582498)

ROC curve and AUC value of all models. by Tiago de Oliveira Barreto (20485207)

“…As for Specificity (82.94%) and ROC-AUC (82.13%), the Multilayer Perceptron with SGD optimizer obtained the highest scores. …”

ELISA analysis revealed a significant decrease in SP (A & B) and CGRP (C & D) protein levels in the corneas and tear fluid of mice treated with 0.5% bupivacaine (BUP) every alternate day for 15 days (administered via subconjunctival injection (SCI) alone or in combination with topical (TOP) application) compared to PBS-treated controls. by Ananya Datta (19932144)

Area under the curve (AUC) for external validation performance. by Junichi Kushioka (12236447)

Quantification of bacterial adhesion revealed a significant decrease in the adhesion of <i>S. aureus</i>, <i>S. epidermidis</i>, and <i>P. aeruginosa</i> on blotted corneas of mice... by Ananya Datta (19932144)

AUC of various models to predict imeglimin efficacy for liver function evaluated by ROC curves. by Naruyoshi Gyoutoku (22537831)

Column charts of WiAUC in therapy and control group at baseline and follow-up. by Felix L. Herr (21544362)

AUC ROC curve. by Dieuwke Luijten (15282736)

Statistical analysis of the AUC measurement. by Esra Ayan (21156015)

“…<p>Analysis indicated that INSv application significantly changed spontaneous calcium activity (IAsp <i>p</i>-value: 0.1290, INSv <i>p</i>-value: 0.0002). The mean AUC decreased in both samples.…”

Area under the ROC Curve (AUC) analysis to predict AIS conversion at 6-months and 1-year following acute cervical tSCI. by Harshit Arora (22008280)

Area under the ROC curve (AUC) analysis to predict neurological severity at 6-months and 1-year following acute cervical tSCI. by Harshit Arora (22008280)

Daily number of adverse outcomes (bars) and area under the precision-recall curve (AUC-PRC) per day of the fullPIERS model. by Guiyou Yang (10259597)

Daily number of adverse outcomes (bars) and area under the precision-recall curve (AUC-PRC) per day of the PIERS-ML model. by Guiyou Yang (10259597)

Acute tear versus chronic-degenerated rotator cuff pathologies are associated with divergent tendon metabolite profiles by Katie J. Sikes (15230030)

“…</p> <p>Acute tears to the rotator cuff were associated with an overall decrease in tendon metabolites. …”

Differences in the muscle force of anterior (A), middle (B), and posterior (C) deltoids in models with and without cuff tears. by Shobu Nakashima (22537717)

Differences in the muscle force of teres minor (A) and long head biceps (B) in models with and without cuff tears. by Shobu Nakashima (22537717)

Differences in glenohumeral joint stability (A) and muscle force of the infraspinatus (B), and subscapularis (C) in models with and without cuff tears. by Shobu Nakashima (22537717)

Feature importance and beeswarm plot determined by mean absolute SHAP values for the DeepSurv model. by Theophilus Gyedu Baidoo (21162511)

AUC statistics comparing statistical trends in control and test populations. by Madeline Jarvis-Cross (22394247)

“…<p>To evaluate statistical trends, we calculated Kendall’s rank correlation coefficient during the pre-critical interval (here, days one to sixty), and compared control (constant temperature, non-epidemic) and warming (warming treatment, epidemic emergence) coefficients across simulations and experimental populations by calculating the area under the curve (AUC) statistic. Values less than 0.5 suggest that a decrease in the statistical metric indicates emergence, while values greater than 0.5 suggest that an increase in the statistical metric indicates emergence, with more extreme values indicating stronger trends. …”

AUC surface with respect to regularization parameters <i>λ</i> and . by Yangsong He (13909371)