The AUC of each model was calculated using 113 ML algorithm. by Xuefen Lin (17785367)

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Relevant literature research content statistics. by Jiren CAO (20442214)

Setup of our Rolling-Dice Experiment and visualization of some of the most relevant facial cues (gaze, head pose, and basic emotions). by Dmitri Bershadskyy (14684464)

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Classical Predictive Coding for motion processing. by Elnaz Nemati (21402730)

Algorithm parameter settings employed in the experiments on simulated data. by Liyan Sun (760586)

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ROC curve analysis of machine learning algorithms with balanced data before tuning (A) and after optimized with hyper parameter tuning (B). by Alemu Birara Zemariam (17540938)

Sensitivity Analysis of the “Swift Effect” Across Matching Algorithms. by James M. Smoliga (9074225)

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Partial dependence plots using models were DVT is predicted by D-dimer and either C3bc, terminal complement complex (TCC) or C-reactive protein (CRP). by Vårin Eiriksdatter Wikan (22379134)

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Abstracts of relevant literature. by Meilin Zhu (688698)

Distribution of plasma concentration of A) C3bc, B) Terminal complement complex (TCC), C) C-reactive protein (CRP) and D) D-dimer with visualization of their corresponding median a... by Vårin Eiriksdatter Wikan (22379134)

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Flow diagram of included and excluded patients. by Vårin Eiriksdatter Wikan (22379134)

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Cohen’s d effect sizes with 95% confidence intervals (CI) for between group comparisons (DVT and non-DVT) of C3bc, TCC, CRP, and D-dimer. by Vårin Eiriksdatter Wikan (22379134)

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Receiver operating characteristics (ROC) curves and their area under the curve (AUC) for A) C3bc and terminal complement complex (TCC), B) C-reactive protein (CRP), C) D-dimer and... by Vårin Eiriksdatter Wikan (22379134)

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Demographic and clinical characteristics of included patients. by Vårin Eiriksdatter Wikan (22379134)

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An example shows how XAI algorithm helps an expert to make a decision. by Shuvo Biswas (21728782)

Expression levels of spinal cord proteins in each group of rats. by Yufeng He (5673119)

Comparison of imbalanced data handling techniques using accuracy and AUC values. by Alemu Birara Zemariam (17540938)

PATH has state-of-the-art performance versus previous binding affinity prediction algorithms. by Yuxi Long (11024307)

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Proportion of positive results in each algorithm and latent prevalences by age (a) and comorbidity (b) groups. by Jia Wei (120974)

Trace plots of estimated prevalence, sensitivity, and specificity of each algorithm of Model-3 in the primary analysis. by Jia Wei (120974)

“…<p>Algorithm [<a href="/article/info:doi/10.1371/journal.pdig.0000936#pdig.0000936.ref001" target="_blank">1</a>] is CAP primary diagnostic codes; Algorithm [<a href="/article/info:doi/10.1371/journal.pdig.0000936#pdig.0000936.ref002" target="_blank">2</a>] is CAP antibiotic indication; Algorithm [<a href="/article/info:doi/10.1371/journal.pdig.0000936#pdig.0000936.ref003" target="_blank">3</a>] is chest X-ray report or CT scan report; Algorithm [<a href="/article/info:doi/10.1371/journal.pdig.0000936#pdig.0000936.ref004" target="_blank">4</a>] is shortness of breath and elevated C-reactive protein levels. …”