{"total":55,"rows":[{"id":"2306.05980","title":"Federated Learning for Medical Image Analysis: A Survey","created":"2023-06-09","cited_by_count":78,"area":null},{"id":"2112.06053","title":"FedSoft: Soft Clustered Federated Learning with Proximal Local Updating","created":"2021-12-11","cited_by_count":46,"area":null},{"id":"2208.03392","title":"Federated Learning for Medical Applications: A Taxonomy, Current Trends, Challenges, and Future Research Directions","created":"2022-08-05","cited_by_count":35,"area":null},{"id":"2211.07893","title":"Federated Learning for Healthcare Domain - Pipeline, Applications and Challenges","created":"2022-11-15","cited_by_count":34,"area":null},{"id":"2107.03901","title":"Federated Learning for Multi-Center Imaging Diagnostics: A Study in Cardiovascular Disease","created":"2021-07-07","cited_by_count":19,"area":null},{"id":"2505.01821","title":"Edge-Cloud Collaborative Computing on Distributed Intelligence and Model Optimization: A Survey","created":"2025-05-03","cited_by_count":14,"area":null},{"id":"2310.09650","title":"Multimodal Federated Learning in Healthcare: a Review","created":"2023-10-14","cited_by_count":13,"area":null},{"id":"2202.07391","title":"Exploring Deep Reinforcement Learning-Assisted Federated Learning for Online Resource Allocation in Privacy-Persevering EdgeIoT","created":"2022-02-15","cited_by_count":12,"area":null},{"id":"2409.12626","title":"Green Federated Learning: A new era of Green Aware AI","created":"2024-09-19","cited_by_count":12,"area":null},{"id":"2403.02619","title":"Training Machine Learning models at the Edge: A Survey","created":"2024-03-05","cited_by_count":11,"area":null},{"id":"2110.08378","title":"FedSLD: Federated Learning with Shared Label Distribution for Medical Image Classification","created":"2021-10-15","cited_by_count":10,"area":null},{"id":"2211.13606","title":"Collaborative Training of Medical Artificial Intelligence Models with non-uniform Labels","created":"2022-11-24","cited_by_count":10,"area":null},{"id":"2305.06217","title":"Patchwork Learning: A Paradigm Towards Integrative Analysis across Diverse Biomedical Data Sources","created":"2023-05-10","cited_by_count":10,"area":null},{"id":"2411.01690","title":"Co-clustering for Federated Recommender System","created":"2024-11-03","cited_by_count":9,"area":null},{"id":"2402.05294","title":"Examining Modality Incongruity in Multimodal Federated Learning for Medical Vision and Language-based Disease Detection","created":"2024-02-07","cited_by_count":8,"area":null},{"id":"2403.01387","title":"A Comprehensive Survey of Federated Transfer Learning: Challenges, Methods and Applications","created":"2024-03-03","cited_by_count":8,"area":null},{"id":"2505.20232","title":"Multimodal Federated Learning With Missing Modalities through Feature Imputation Network","created":"2025-05-26","cited_by_count":8,"area":null},{"id":"2203.05759","title":"Federated Remote Physiological Measurement with Imperfect Data","created":"2022-03-11","cited_by_count":7,"area":null},{"id":"2211.02906","title":"ON-DEMAND-FL: A Dynamic and Efficient Multi-Criteria Federated Learning Client Deployment Scheme","created":"2022-11-05","cited_by_count":7,"area":null},{"id":"2110.04160","title":"Federated Learning for Big Data: A Survey on Opportunities, Applications, and Future Directions","created":"2021-10-08","cited_by_count":6,"area":null},{"id":"2112.10001","title":"Cross-Domain Federated Learning in Medical Imaging","created":"2021-12-18","cited_by_count":6,"area":null},{"id":"2401.03609","title":"Multi-Modal Federated Learning for Cancer Staging over Non-IID Datasets with Unbalanced Modalities","created":"2024-01-07","cited_by_count":6,"area":null},{"id":"2504.08584","title":"Boosting multi-demographic federated learning for chest radiograph analysis using general-purpose self-supervised representations","created":"2025-04-11","cited_by_count":6,"area":null},{"id":"2309.07085","title":"Mitigating Group Bias in Federated Learning for Heterogeneous Devices","created":"2023-09-13","cited_by_count":5,"area":null},{"id":"2407.08648","title":"CAR-MFL: Cross-Modal Augmentation by Retrieval for Multimodal Federated Learning with Missing Modalities","created":"2024-07-11","cited_by_count":5,"area":null},{"id":"2501.11388","title":"UniTrans: A Unified Vertical Federated Knowledge Transfer Framework for Enhancing Cross-Hospital Collaboration","created":"2025-01-20","cited_by_count":5,"area":null},{"id":"2201.09384","title":"A Comprehensive Survey on Federated Learning: Concept and Applications","created":"2022-01-23","cited_by_count":4,"area":null},{"id":"2211.01805","title":"FedMint: Intelligent Bilateral Client Selection in Federated Learning with Newcomer IoT Devices","created":"2022-10-31","cited_by_count":4,"area":null},{"id":"2312.04688","title":"Federated Learning for 6G: Paradigms, Taxonomy, Recent Advances and Insights","created":"2023-12-07","cited_by_count":4,"area":null},{"id":"2104.02425","title":"The Duo of Artificial Intelligence and Big Data for Industry 4.0: Review of Applications, Techniques, Challenges, and Future Research Directions","created":"2021-04-06","cited_by_count":3,"area":null},{"id":"2210.13289","title":"Secure and Trustworthy Artificial Intelligence-Extended Reality (AI-XR) for Metaverses","created":"2022-10-24","cited_by_count":3,"area":null},{"id":"2303.10624","title":"PFSL: Personalized & Fair Split Learning with Data & Label Privacy for thin clients","created":"2023-03-19","cited_by_count":3,"area":null},{"id":"2310.10665","title":"Privacy Preservation in Artificial Intelligence and Extended Reality (AI-XR) Metaverses: A Survey","created":"2023-09-19","cited_by_count":3,"area":null},{"id":"2103.01196","title":"Sentiment Analysis of Users' Reviews on COVID-19 Contact Tracing Apps with a Benchmark Dataset","created":"2021-03-01","cited_by_count":2,"area":null},{"id":"2203.12803","title":"A Two-Stage Federated Transfer Learning Framework in Medical Images Classification on Limited Data: A COVID-19 Case Study","created":"2022-03-24","cited_by_count":2,"area":null},{"id":"2209.09642","title":"A Secure Healthcare 5.0 System Based on Blockchain Technology Entangled with Federated Learning Technique","created":"2022-09-16","cited_by_count":2,"area":null},{"id":"2303.07067","title":"Cross-device Federated Learning for Mobile Health Diagnostics: A First Study on COVID-19 Detection","created":"2023-03-13","cited_by_count":2,"area":null},{"id":"2404.13348","title":"Socialized Learning: A Survey of the Paradigm Shift for Edge Intelligence in Networked Systems","created":"2024-04-20","cited_by_count":2,"area":null},{"id":"2501.17512","title":"A survey on Clustered Federated Learning: Taxonomy, Analysis and Applications","created":"2025-01-29","cited_by_count":2,"area":null},{"id":"2508.20414","title":"Federated Learning for Large Models in Medical Imaging: A Comprehensive Review","created":"2025-08-28","cited_by_count":2,"area":null},{"id":"2210.16142","title":"Federated Learning for Chronic Obstructive Pulmonary Disease Classification with Partial Personalized Attention Mechanism","created":"2022-10-28","cited_by_count":1,"area":null},{"id":"2503.10262","title":"A Multi-Modal Federated Learning Framework for Remote Sensing Image Classification","created":"2025-03-13","cited_by_count":1,"area":null},{"id":"2504.20656","title":"Federated learning, ethics, and the double black box problem in medical AI","created":"2025-04-29","cited_by_count":1,"area":null},{"id":"2512.08314","title":"Minimizing Layerwise Activation Norm Improves Generalization in Federated Learning","created":"2025-12-09","cited_by_count":1,"area":null},{"id":"2109.01669","title":"Multimodal Detection of COVID-19 Symptoms using Deep Learning & Probability-based Weighting of Modes","created":"2021-09-03","cited_by_count":0,"area":null},{"id":"2408.12029","title":"Federated Diabetes Prediction in Canadian Adults Using Real-world Cross-Province Primary Care Data","created":"2024-08-21","cited_by_count":0,"area":null},{"id":"2409.15898","title":"FedRepOpt: Gradient Re-parametrized Optimizers in Federated Learning","created":"2024-09-24","cited_by_count":0,"area":null},{"id":"2503.00407","title":"Asynchronous Personalized Federated Learning through Global Memorization","created":"2025-03-01","cited_by_count":0,"area":null},{"id":"2504.01882","title":"CO-DEFEND: Continuous Decentralized Federated Learning for Secure DoH-Based Threat Detection","created":"2025-04-02","cited_by_count":0,"area":null},{"id":"2505.07575","title":"Personalized Federated Learning under Model Dissimilarity Constraints","created":"2025-05-12","cited_by_count":0,"area":null},{"id":"2510.09155","title":"Federated Data Analytics for Cancer Immunotherapy: A Privacy-Preserving Collaborative Platform for Patient Management","created":"2025-10-10","cited_by_count":0,"area":null},{"id":"2512.10701","title":"HybridVFL: Disentangled Feature Learning for Edge-Enabled Vertical Federated Multimodal Classification","created":"2025-12-11","cited_by_count":0,"area":null},{"id":"2606.23091","title":"FLFL: Federated Latent Factor Learning for Private Recovery of Spatio-Temporal Signals","created":"2026-06-22","cited_by_count":0,"area":null},{"id":"2606.23871","title":"Federated Survival Analysis in Healthcare: A Multi-Model Evaluation on Cross-Institutional Heterogeneous Breast Cancer Data","created":"2026-06-22","cited_by_count":0,"area":null},{"id":"2609.22932","title":"Joint Domain-Class Modeling for Federated Learning Under Feature Skew","created":"2026-09-19","cited_by_count":0,"area":null}],"next_cursor":null}