(22522087), M. A. T., (22522090), I. A., (22522093), M. A., & (22522096), H. A. (2025). Ablation study quantifying the individual contribution of each core component to the performance of the hybrid framework. The study systematically evaluates three configurations: A baseline Standard SVM without hyperparameter optimization, the SVM optimized with the proposed modified Particle Swarm Optimization (PSO) algorithm and the Full Hybrid Model. The findings indicate that the PSO optimization can be used to gain a significant performance improvement in all metrics (e.g., + 4.4% accuracy, + 3.5% AUC) which proves the importance of the pivot role of hyperparameter tuning. Incorporating the SHAP module that introduces explainability does not lead to degradation of performance, as it proves that the framework provides high accuracy without compromising interpretability, which is one of the conditions that must be fulfilled when adopting the framework by a healthcare institution.
توثيق أسلوب شيكاغو (الطبعة السابعة عشر)(22522087), Medhat A. Tawfeek, Ibrahim Alrashdi (22522090), Madallah Alruwaili (22522093), و Hisham Allahem (22522096). Ablation Study Quantifying the Individual Contribution of Each Core Component to the Performance of the Hybrid Framework. The Study Systematically Evaluates Three Configurations: A Baseline Standard SVM Without Hyperparameter Optimization, the SVM Optimized with the Proposed Modified Particle Swarm Optimization (PSO) Algorithm and the Full Hybrid Model. The Findings Indicate That the PSO Optimization Can Be Used to Gain a Significant Performance Improvement in All Metrics (e.g., + 4.4% Accuracy, + 3.5% AUC) Which Proves the Importance of the Pivot Role of Hyperparameter Tuning. Incorporating the SHAP Module That Introduces Explainability Does Not Lead to Degradation of Performance, as It Proves That the Framework Provides High Accuracy Without Compromising Interpretability, Which Is One of the Conditions That Must Be Fulfilled When Adopting the Framework by a Healthcare Institution. 2025.
توثيق جمعية اللغة المعاصرة MLA (الإصدار التاسع)(22522087), Medhat A. Tawfeek, et al. Ablation Study Quantifying the Individual Contribution of Each Core Component to the Performance of the Hybrid Framework. The Study Systematically Evaluates Three Configurations: A Baseline Standard SVM Without Hyperparameter Optimization, the SVM Optimized with the Proposed Modified Particle Swarm Optimization (PSO) Algorithm and the Full Hybrid Model. The Findings Indicate That the PSO Optimization Can Be Used to Gain a Significant Performance Improvement in All Metrics (e.g., + 4.4% Accuracy, + 3.5% AUC) Which Proves the Importance of the Pivot Role of Hyperparameter Tuning. Incorporating the SHAP Module That Introduces Explainability Does Not Lead to Degradation of Performance, as It Proves That the Framework Provides High Accuracy Without Compromising Interpretability, Which Is One of the Conditions That Must Be Fulfilled When Adopting the Framework by a Healthcare Institution. 2025.