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)

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

Feature engineering. by Youli Jiang (15249070)

TITAN decreaser diatom heatmap. by Brent J. Bellinger (21156150)

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

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Data Sheet 1_Emotional prompting amplifies disinformation generation in AI large language models.docx by Rasita Vinay (21006911)

“…Introduction<p>The emergence of artificial intelligence (AI) large language models (LLMs), which can produce text that closely resembles human-written content, presents both opportunities and risks. …”

Analysis of tea output value distribution and growth- decrease rate of provinces. by Kun Qin (177235)

<b>Supporting data for manuscript</b> "<b>Voluntary locomotion induces an early and remote hemodynamic decrease in the large cerebral veins</b>" by Kira Shaw (18796168)

“…<p dir="ltr">The CSV file 'Eyreetal_DrainingVein_SourceData' contains the averaged time series traces and extracted metrics from individual experiments used across Figures 1-5 in the manuscript "Voluntary locomotion induces an early and remote hemodynamic decrease in the large cerebral veins". The following acronyms included in the CSV file are defined as follows: Hbt is total hemoglobin, Art is artery region, DV is draining vein region, WV is whisker vein region, SEM is standard error mean, TS is time series, max peak is maximum peak, min peak is minima, AUC is area under the curve, WT is wild-type, AD is Alzheimer's disease, ATH is atherosclerosis and MIX is mixed AD/atherosclerosis. …”

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)

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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)

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Feasibility of AI-powered assessment scoring: Can large language models replace human raters? by Michael Jaworski III (22156096)

Decrease in loss during the training process. by Muhammad Idrees (92773)

TITAN decreaser macroinvertebrate heatmap Heatmap of sensitive (i.e., <i>z-</i>) macroinvertebrate taxa (y-axis) to at least one of the five stressors, in decreasing order of numbe... by Brent J. Bellinger (21156150)

Maximum IFN concentrations are decreased in severe patients. by Sonia T. Gazeau (21512764)

Multivariate regression analysis to explain the decrease in visibility and palpability. by Miharu Matsumoto (21304390)

ROC Curve for the Best Model (AUC = 0.92). by Mudhafar Jalil Jassim Ghrabat (22177655)

List of network connections predictive of individual SoF values, together with their β weights, in decreasing order. by Yinan Xu (12440894)

“…<p>List of network connections predictive of individual SoF values, together with their β weights, in decreasing order.…”

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)

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