Performance Comparison of Fed_avg and FLPMDP Models.

Performance Comparison of Fed_avg and FLPMDP Models.

<p>Performance Comparison of Fed_avg and FLPMDP Models.</p>

محفوظ في:

التفاصيل البيبلوغرافية
المؤلف الرئيسي:	Syed Mohsin Bokhari (21702906) (author)
مؤلفون آخرون:	Sarmad Sohaib (21273402) (author), Muhammad Shafi (7168253) (author)
منشور في:	2025
الموضوعات:	Cell Biology Neuroscience Biotechnology Mental Health Biological Sciences not elsewhere classified Information Systems not elsewhere classified matthews correlation coefficient four experimental setups 646 recordings indicates time arrhythmia detection sr ), respectively iid data conditions flpmdp approach achieves federated baseline models large ecg dataset feature fusion techniques personalized federated learning personalized models flpmdp ), federated learning diagnosing arrhythmia gsvt ), flpmdp recorded data confidentiality data privacy xlink "> step forward sinus rhythm sinus bradycardia paper presents modern healthcare model strength lead electrocardiogram kappa score highly pertinent facing non enabling secure empirical experiment compliant solution comparative analysis 71 %.
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مواد مشابهة

Confusion matrix of Fed_avg Model with Features Fusion.
حسب: Syed Mohsin Bokhari (21702906)
منشور في: (2025)

Confusion matrix of FLPMDP model with Features Fusion.
حسب: Syed Mohsin Bokhari (21702906)
منشور في: (2025)

Computational overhead comparison between centralized learning and FL-based approaches.
حسب: Syed Mohsin Bokhari (21702906)
منشور في: (2025)

Performance comparison with existing models.
حسب: Syed Mohsin Bokhari (21702906)
منشور في: (2025)

Performance comparison of GRU model with and without Feature Fusion.
حسب: Syed Mohsin Bokhari (21702906)
منشور في: (2025)

Hardware and software specifications used in the experimental setup.
حسب: Syed Mohsin Bokhari (21702906)
منشور في: (2025)

Model accuracy across different classes.
حسب: Syed Mohsin Bokhari (21702906)
منشور في: (2025)

Confusion matrix of GRU model with Features Fusion.
حسب: Syed Mohsin Bokhari (21702906)
منشور في: (2025)

Confusion matrix of GRU without Feature Fusion Model.
حسب: Syed Mohsin Bokhari (21702906)
منشور في: (2025)

The proposed framework.
حسب: Syed Mohsin Bokhari (21702906)
منشور في: (2025)

The structure of a typical ECG signal.
حسب: Syed Mohsin Bokhari (21702906)
منشور في: (2025)

Definitions of non-standard abbreviations.
حسب: Pan Li (335711)
منشور في: (2025)

Dissecting key mechanisms governing circadian and vigilance state regulation of seizure-induced SANC firing patterns.
حسب: Pan Li (335711)
منشور في: (2025)

Regulation of seizure-induced SANC firing patterns by circadian rhythms and vigilance states.
حسب: Pan Li (335711)
منشور في: (2025)

Neurocardiogenic mechanisms underlying seizure-induced arrhythmias in SANC excitation patterns.
حسب: Pan Li (335711)
منشور في: (2025)

Transient autonomic changes are not required to trigger ictal and postictal sinus arrhythmias.
حسب: Pan Li (335711)
منشور في: (2025)

Schematic of a mouse SANC model incorporating circadian and vigilance state variations.
حسب: Pan Li (335711)
منشور في: (2025)

Clinical and experimental measurements of seizure-induced sinus arrhythmias and mortality.
حسب: Pan Li (335711)
منشور في: (2025)

The accuracy of MNIST dataset under FedAvg, FedProx, and SCAFFOLD.
حسب: Pan Wang (198097)
منشور في: (2025)

The accuracy of MNIST dataset under FedAvg, FedProx, and SCAFFOLD.
حسب: Pan Wang (198097)
منشور في: (2025)

Comparison of MNIST with different intervals under FedAvg, FedProx and SCAFFOLD.
حسب: Pan Wang (198097)
منشور في: (2025)

The accuracy of TodayNews dataset under FedAvg, FedProx, and SCAFFOLD.
حسب: Pan Wang (198097)
منشور في: (2025)

The accuracy of FashionMNIST dataset under FedAvg, FedProx, and SCAFFOLD.
حسب: Pan Wang (198097)
منشور في: (2025)

The accuracy of FashionMNIST dataset under FedAvg, FedProx, and SCAFFOLD.
حسب: Pan Wang (198097)
منشور في: (2025)

The accuracy of FashionMNIST dataset under FedAvg, FedProx, and SCAFFOLD.
حسب: Pan Wang (198097)
منشور في: (2025)

Comparison of FashionMNIST with different intervals under FedAvg, FedProx and SCAFFOLD.
حسب: Pan Wang (198097)
منشور في: (2025)

Comparison of TodayNew with different intervals under FedAvg, FedProx and SCAFFOLD.
حسب: Pan Wang (198097)
منشور في: (2025)

Data Sheet 1_A meta-learning-based robust federated learning for diagnosing lung adenocarcinoma and tuberculosis granulomas.docx
حسب: Yuyao Chen (7863890)
منشور في: (2025)

Data Sheet 1_FedCMC: a federated learning model with contribution fairness based on multi-center core data extraction for assessing the myometrial invasion status of endometrial cancer.docx
حسب: Yuping Li (157863)
منشور في: (2025)

Supplementary file 1_Leveraging real-world data for safety signal detection and risk management in pre- and post-market settings.docx
حسب: Kathleen M. Gavin (10871592)
منشور في: (2025)

Data Sheet 1_ECG-XPLAIM: eXPlainable Locally-adaptive Artificial Intelligence Model for arrhythmia detection from large-scale electrocardiogram data.pdf
حسب: Panteleimon Pantelidis (12499942)
منشور في: (2025)

Inclusion and exclusion criteria.
حسب: Ryo Tateishi (22138994)
منشور في: (2025)

Study flowchart of the LINQ2-HF trial.
حسب: Ryo Tateishi (22138994)
منشور في: (2025)

The overview of the schedule for the LINQ2-HF trial.
حسب: Ryo Tateishi (22138994)
منشور في: (2025)

Incomplete Right Bundle Branch Block: A Narrative Review of Clinical Relevance, Diagnostic Pitfalls, and Prognostic Implications
حسب: Adis journals on behalf of: (17448228)
منشور في: (2025)

Comparison with state-of-the-art methods.
حسب: Hassan Kamran (21782056)
منشور في: (2025)

Impact of pretraining on FedGAN performance.
حسب: Hassan Kamran (21782056)
منشور في: (2025)

Summary of most relevant paper.
حسب: Hassan Kamran (21782056)
منشور في: (2025)

Comparative analysis of recent privacy-preserving medical image generation approaches.
حسب: Hassan Kamran (21782056)
منشور في: (2025)

Federated learning generator loss variance.
حسب: Hassan Kamran (21782056)
منشور في: (2025)