Initial parameter settings for the optimization algorithms. حسب Doaa Sami Khafaga (21463870)

Bar chart comparing the average fitness values of various feature selection algorithms. حسب Doaa Sami Khafaga (21463870)

Box plots with swarm overlays for six feature selection algorithms, annotated with mean and standard deviation values. حسب Doaa Sami Khafaga (21463870)

The flowchart showing the optimization process of the hybrid methods using BEOSA as the base algorithm and SA and FFA as integrated algorithms. حسب Olaide N. Oyelade (14047002)

الموضوعات:

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

Line plots showing performance trends for six evaluation metrics across CNN combined with different bio-inspired optimization algorithms. حسب Doaa Sami Khafaga (21463870)

Correlation heatmap of performance scores among different feature selection algorithms: bOcOA, bPSO, bGWO, bFA, bGA, and bWAO. حسب Doaa Sami Khafaga (21463870)

Density distribution plot of performance metrics for various feature selection algorithms: bOcOA, bPSO, bGWO, bFA, bGA, and bWAO. حسب Doaa Sami Khafaga (21463870)

Flowchart of the general algorithm for one trial. حسب Junying Wang (509009)

Simulation parameters. حسب Hend Bayoumi (22693738)

Hierarchical clustering to infer a binary tree with <i>K</i> = 4 sampled populations. حسب Tristan Mary-Huard (3864)

The performance of our proposed method in four scenarios (I to IV) uses simulated data that mimics real-world data distribution with the complete version. حسب Yi-Wen Hsiao (13767916)

الموضوعات:

Performance of our proposed method in four scenarios (I to IV) using naïve simulated data with the complete version. حسب Yi-Wen Hsiao (13767916)

الموضوعات:

Homomorphic binary tree. حسب Jianhua He (341366)

RMSE on the test data when fitting (logistic) quadratic models to binary data across increasing measurement error values . حسب Jakub Stoklosa (3315042)

Joint Detection of Change Points in Multichannel Single-Molecule Measurements حسب Hugh Wilson (11797444)

الموضوعات:

Melanoma Skin Cancer Detection Using Deep Learning Methods and Binary GWO Algorithm حسب Hussein Ali Bardan (21976208)

"…By leveraging the binary GWO algorithm to optimize the feature selection </p><p dir="ltr">process and CNNs for image classification, the proposed approach reduces computational costs while increasing </p><p dir="ltr">classification accuracy. …"

Classification baseline performance. حسب Doaa Sami Khafaga (21463870)

"…Crucially, this optimization also results in a substantial clinical performance gain, with sensitivity increasing from 86.02% to 98.34% (+12.32%), specificity rising from 86.53% to 98.14% (+11.61%), and the false negative rate being significantly reduced, thereby enhancing diagnostic reliability in critical scenarios. …"

Feature selection results. حسب Doaa Sami Khafaga (21463870)

"…Crucially, this optimization also results in a substantial clinical performance gain, with sensitivity increasing from 86.02% to 98.34% (+12.32%), specificity rising from 86.53% to 98.14% (+11.61%), and the false negative rate being significantly reduced, thereby enhancing diagnostic reliability in critical scenarios. …"

ANOVA test result. حسب Doaa Sami Khafaga (21463870)

"…Crucially, this optimization also results in a substantial clinical performance gain, with sensitivity increasing from 86.02% to 98.34% (+12.32%), specificity rising from 86.53% to 98.14% (+11.61%), and the false negative rate being significantly reduced, thereby enhancing diagnostic reliability in critical scenarios. …"