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. …”

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

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)

High-Temperature Resistance, Lightweight, and Thermally Insulating Silica Aerogel via Doping Hollow Silica Nanoparticles by Mingyang Yang (1405321)

High-Temperature Resistance, Lightweight, and Thermally Insulating Silica Aerogel via Doping Hollow Silica Nanoparticles by Mingyang Yang (1405321)

High-Temperature Resistance, Lightweight, and Thermally Insulating Silica Aerogel via Doping Hollow Silica Nanoparticles by Mingyang Yang (1405321)

High-Temperature Resistance, Lightweight, and Thermally Insulating Silica Aerogel via Doping Hollow Silica Nanoparticles by Mingyang Yang (1405321)

High-Temperature Resistance, Lightweight, and Thermally Insulating Silica Aerogel via Doping Hollow Silica Nanoparticles by Mingyang Yang (1405321)

High-Temperature Resistance, Lightweight, and Thermally Insulating Silica Aerogel via Doping Hollow Silica Nanoparticles by Mingyang Yang (1405321)

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)

Continuous Viscoelasticity Measurement of Cell Spheroids via Microfluidic Electrical Aspiration by Heyi Chen (19930197)

Subjects:

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. …”