Accuracy Results from Random Forest and Binary Logistic Regression Models by Data Types. by Anis Ben Ghorbal (22521828)

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Information Value Scores (Binary Logistic Regression) and Feature Importance Scores (Random Forest) Across Features (for IVs from LR, a bar with dashed border indicates a significa... by Anis Ben Ghorbal (22521828)

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Telehealth. by Anis Ben Ghorbal (22521828)

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Characteristics of Highly Agreed Participants among Disability Subgroups, Odds Ratio (OR), and 95% Confidence Interval (CI). by Anis Ben Ghorbal (22521828)

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Kernel Density Plot of Effort Expectancy Scores. by Anis Ben Ghorbal (22521828)

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Frequency and Density plot of features Across Classes of Ease of using the telehealth system “Effort Expectancy”. by Anis Ben Ghorbal (22521828)

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ROC Curve and Classification Thresholds [33–36]. by Anis Ben Ghorbal (22521828)

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Characteristics of Participant by the ease of using the telehealth system “Effort Expectancy”. by Anis Ben Ghorbal (22521828)

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Random Forest Framework. by Anis Ben Ghorbal (22521828)

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Logistic Classification Model of the Effort Expectancy. by Anis Ben Ghorbal (22521828)

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Influence of underlying networks on the performance of Graph CNNs trained gene expression data. by Halima Alachram (11570633)

Thesis-RAMIS-Figs_Slides by Felipe Santibañez-Leal (10967991)

“…<br><br>Finally, although the developed concepts, ideas and algorithms have been developed for inverse problems in geostatistics, the results are applicable to a wide range of disciplines where similar sampling problems need to be faced, included but not limited to design of communication networks, optimal integration and communication of swarms of robots and drones, remote sensing.…”