One advantage of our algorithm is that it is not binary in nature. حسب Yong Kuk Kim (13955214)

Several loop patterns found in binary code. حسب Alba Pedro-Zapater (8600382)

Calibration curves for the test set of four models. حسب Meng Cao (105914)

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ROC curves for the test set of four models. حسب Meng Cao (105914)

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Performance metrics of the models on the training and test set. حسب Meng Cao (105914)

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<i>hi</i>PRS algorithm process flow. حسب Michela C. Massi (14599915)

SHAP bar plot. حسب Meng Cao (105914)

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Display of the web prediction interface. حسب Meng Cao (105914)

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Sample screening flowchart. حسب Meng Cao (105914)

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Descriptive statistics for variables. حسب Meng Cao (105914)

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SHAP summary plot. حسب Meng Cao (105914)

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Random forest model performs better than support vector machine algorithms and when it primarily uses spontaneous photopic ERG of 60-s duration in humans. حسب Ramsés Noguez Imm (6658637)

Spontaneous ERG-based random forest model discriminates control and disease cases in rodent models of obesity and type 1 diabetes and predicts disease evolution in the type 1 diabe... حسب Ramsés Noguez Imm (6658637)

Sample image for illustration. حسب Indhumathi S. (19173013)

"…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …"

Comparison analysis of computation time. حسب Indhumathi S. (19173013)

"…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …"

Process flow diagram of CBFD. حسب Indhumathi S. (19173013)

"…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …"

Precision recall curve. حسب Indhumathi S. (19173013)

"…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …"

Quadratic polynomial in 2D image plane. حسب Indhumathi S. (19173013)

"…The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …"

Image 1_A multimodal AI-driven framework for cardiovascular screening and risk assessment in diverse athletic populations: innovations in sports cardiology.png حسب Minjin Guo (22751300)

"…</p>Results and Discussion<p>Experimental evaluation across varied athlete cohorts demonstrates superior performance in risk stratification accuracy, diagnostic plausibility, and model transparency compared to traditional screening algorithms. …"

Table 1_Heavy metal biomarkers and their impact on hearing loss risk: a machine learning framework analysis.docx حسب Ali Nabavi (21097424)