Data_Sheet_1_Development and Validation of a Novel Risk Prediction Model Using Recursive Feature Elimination Algorithm for Acute-on-Chronic Liver Failure in Chronic Hepatitis B Pat... حسب Mingxue Yu (10273496)

Data_Sheet_2_Development and Validation of a Novel Risk Prediction Model Using Recursive Feature Elimination Algorithm for Acute-on-Chronic Liver Failure in Chronic Hepatitis B Pat... حسب Mingxue Yu (10273496)

Proposed reinforcement learning architecture. حسب Enoch Solomon (21416703)

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The images shown correspond the downscaled images an agent receives in Unity environment. حسب Enoch Solomon (21416703)

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Average success rate (%) of the test experiment on ViZDoom and Unity environments. حسب Enoch Solomon (21416703)

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Models’ performance without optimization. حسب Muhammad Usman Tariq (11022141)

"…Analytic approaches, both predictive and retrospective in nature, were used to interpret the data. Our primary objective was to determine the most effective model for predicting COVID-19 cases in the United Arab Emirates (UAE) and Malaysia. …"

Iteration curve of the optimization process. حسب Meijun Shang (22806461)

"…The load-bearing mechanism of the proposed steel platform was analyzed theoretically, and finite element analysis (FEA) was employed to evaluate the stresses and deflections of key members. A particle swarm optimization (PSO) algorithm was integrated with the FEA model to optimize the cross-sectional dimensions of the primary beams, secondary beams, and foundation boxes, achieving a balance between load-bearing capacity and cost efficiency. …"

Data_Sheet_1_Prediction of patient choice tendency in medical decision-making based on machine learning algorithm.pdf حسب Yuwen Lyu (14330781)

"…In conjunction with the study's data characteristics, three ML classification algorithms, decision tree (DT), k-nearest neighbor (KNN), and support vector machine (SVM), were used to predict patients' medical decision-making tendency, and the performance of the three types of algorithms was compared.…"

The relationship between the prevalence of PE and failure rate of each diagnostic strategy. حسب Geert-Jan Geersing (331049)

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Forest plot of failure rate and efficiency of the diagnostic strategies across healthcare settings. حسب Geert-Jan Geersing (331049)

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The relationship between the prevalence of PE and efficiency of each diagnostic strategy. حسب Geert-Jan Geersing (331049)

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Patient characteristics across different healthcare settings. حسب Geert-Jan Geersing (331049)

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Sensitivity and specificity of diagnostic strategies across healthcare settings. حسب Geert-Jan Geersing (331049)

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Comparative analysis of DDcGAN-GSOM’s True Positive Rate, False Alarm Rate, and Specificity. حسب Nanavath Kiran Singh Nayak (22184565)

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Architecture of proposed system model. حسب Nanavath Kiran Singh Nayak (22184565)

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F1-score analysis of DDcGAN-GSOM with existing methods. حسب Nanavath Kiran Singh Nayak (22184565)

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Accuracy analysis of DDcGAN-GSOM with existing techniques. حسب Nanavath Kiran Singh Nayak (22184565)

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Network simulation of the proposed method. حسب Nanavath Kiran Singh Nayak (22184565)

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Simulation parameters of SDN network. حسب Nanavath Kiran Singh Nayak (22184565)

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Generator loss of the proposed method. حسب Nanavath Kiran Singh Nayak (22184565)

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