Browse studies, page 358

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• Federated Learning in Risk Prediction: A Primer and Application to COVID-19-Associated Acute Kidney Injury Nephron, 2023
• Data visiting governance: a conceptual framework Human genomics, 2025
• Retinal Scans and Data Sharing: The Privacy and Scientific Development Equilibrium Mayo Clinic proceedings. Digital health, 2023
• Artificial Intelligence in Rheumatology: Clinical Applications in Rheumatoid Arthritis, Osteoarthritis, and Systemic Lupus Erythematosus Cureus, 2025
• Application of privacy protection technology to healthcare big data Digital health, 2024
• A comprehensive review on federated learning based models for healthcare applications Artificial intelligence in medicine, 2023
• Federated Learning for Medical Image Analysis with Deep Neural Networks Diagnostics (Basel, Switzerland), 2023
• Challenges and future directions of secure federated learning: a survey Frontiers of computer science, 2022
• Creating a data exchange strategy for radiotherapy research: towards federated databases and anonymised public datasets Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology, 2014
• Blueprint for harmonising unstandardised disease registries to allow federated data analysis: prepare for the future ERJ open research, 2022
• Artificial intelligence and transforming cancer care Discover oncology, 2026
• Can we share models if sharing data is not an option? Patterns (New York, N.Y.), 2022
• The Promise of AI in Detection, Diagnosis, and Epidemiology for Combating COVID-19: Beyond the Hype Frontiers in artificial intelligence, 2021
• Advances and challenges in single-cell RNA sequencing data analysis: a comprehensive review Briefings in bioinformatics, 2026
• Artificial Intelligence in Health in 2018: New Opportunities, Challenges, and Practical Implications Yearbook of medical informatics, 2019
• Artificial intelligence-enhanced ECG interpretation: a new era for electrocardiography? Giornale italiano di cardiologia (2006), 2025
• In the Pursuit of Privacy: The Promises and Predicaments of Federated Learning in Healthcare Frontiers in artificial intelligence, 2021
• Privacy-preserving techniques for decentralized and secure machine learning in drug discovery Drug discovery today, 2023
• Artificial Intelligence and Digital Biomarkers in Hepatology: Critical Perspectives, Emerging Evidence, and Future Directions Cureus, 2025
• Deep Learning in Otolaryngology: A Narrative Review JAMA otolaryngology-- head & neck surgery, 2026
• Artificial intelligence and wearable sensors in sports injury risk prediction: current status and future perspectives Annals of medicine, 2026
• Deep Reinforcement Learning for Sustainable Urban Mobility: A Bibliometric and Empirical Review Sensors (Basel, Switzerland), 2026
• Integrating Artificial Intelligence in Next-Generation Sequencing: Advances, Challenges, and Future Directions Current issues in molecular biology, 2025
• Legal aspects of privacy-enhancing technologies in genome-wide association studies and their impact on performance and feasibility Genome biology, 2024
• Federated Learning: Breaking Down Barriers in Global Genomic Research Genes, 2024
• Privacy-preserving decentralized learning methods for biomedical applications Computational and structural biotechnology journal, 2024
• The Role of Artificial Intelligence in the Diagnosis of Melanoma Cureus, 2024
• Systematic review of trends in deep learning for UAV cybersecurity Frontiers in artificial intelligence, 2026
• Multimodal Federated Learning: A Survey Sensors (Basel, Switzerland), 2023
• Federated Analysis of Neuroimaging Data: A Review of the Field Neuroinformatics, 2022
• Federated learning for generating synthetic data: a scoping review International journal of population data science, 2023
• Advocating for neurodata privacy and neurotechnology regulation Nature protocols, 2023
• Federated Learning in Ocular Imaging: Current Progress and Future Direction Diagnostics (Basel, Switzerland), 2022
• Systematic Review of Privacy-Preserving Distributed Machine Learning From Federated Databases in Health Care JCO clinical cancer informatics, 2020
• Reviewing Federated Machine Learning and Its Use in Diseases Prediction Sensors (Basel, Switzerland), 2023
• Federated learning: Overview, strategies, applications, tools and future directions Heliyon, 2024
• A review on federated learning in computational pathology Computational and structural biotechnology journal, 2024
• Harnessing AI for enhanced evidence-based laboratory medicine (EBLM) Clinica chimica acta; international journal of clinical chemistry, 2025
• Federated Machine Learning, Privacy-Enhancing Technologies, and Data Protection Laws in Medical Research: Scoping Review Journal of medical Internet research, 2023
• Integration of large language models and federated learning Patterns (New York, N.Y.), 2024
• Training Strategies for Radiology Deep Learning Models in Data-limited Scenarios Radiology. Artificial intelligence, 2021
• Applications of Federated Learning in Mobile Health: Scoping Review Journal of medical Internet research, 2023
• Artificial intelligence in rare diseases: toward clinical impact Trends in pharmacological sciences, 2025
• Navigating the Evolution of Digital Twins Research through Keyword Co-Occurence Network Analysis Sensors (Basel, Switzerland), 2024
• The AI revolution in glaucoma: Bridging challenges with opportunities Progress in retinal and eye research, 2024
• Research Progress in Artificial Intelligence for Central Serous Chorioretinopathy: A Systematic Review Ophthalmology and therapy, 2025
• Federated Learning in Public Health: A Systematic Review of Decentralized, Equitable, and Secure Disease Prevention Approaches Healthcare (Basel, Switzerland), 2025
• Federated learning for medical imaging radiology The British journal of radiology, 2023
• Privacy preserving technology in ophthalmology Current opinion in ophthalmology, 2024
• Ethics and responsible AI deployment Frontiers in artificial intelligence, 2024
• A systematic review of privacy-preserving methods deployed with blockchain and federated learning for the telemedicine Healthcare analytics (New York, N.Y.), 2023
• Medical Imaging Applications of Federated Learning Diagnostics (Basel, Switzerland), 2023
• Novel technical and privacy-preserving technology for artificial intelligence in ophthalmology Current opinion in ophthalmology, 2022
• Artificial Intelligence and Advanced Digital Health for Hypertension: Evolving Tools for Precision Cardiovascular Care Medicina (Kaunas, Lithuania), 2025
• Artificial intelligence: opportunities in lung cancer Current opinion in oncology, 2022
• Current AI technologies in cancer diagnostics and treatment Molecular cancer, 2025
• Privacy-preserving artificial intelligence in healthcare: Techniques and applications Computers in biology and medicine, 2023
• Traumatic brain injury: progress and challenges in prevention, clinical care, and research The Lancet. Neurology, 2022
• Artificial Intelligence in Dentistry: Chances and Challenges Journal of dental research, 2020
• Scaling Law Analysis in Federated Learning: How to Select the Optimal Model Size? arXiv, 2025
• SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies arXiv, 2026
• Enhancing the Privacy of Federated Learning with Sketching arXiv, 2019
• Privacy-Preserving Feature Valuation in Vertical Federated Learning Using Shapley-CMI and PSI Permutation arXiv, 2025
• Optimizing Federated Learning by Entropy-Based Client Selection arXiv, 2024
• Federated Deep Reinforcement Learning for Privacy-Preserving Robotic-Assisted Surgery IEEE ICDCS 2025 45th IEEE International Conference on Distributed Computing Systems. Workshop on Federated and Privacy Preserving AI in Biomedical Applications (FPPAI), Glasgow, United Kingdom, 2025
• Comparative Evaluation of Clustered Federated Learning Methods The 2nd IEEE International Conference on Federated Learning Technologies and Applications (FLTA24), Sep 2024, Valencia (Espagne), Spain, 2024
• Federated Transfer Learning with Differential Privacy arXiv, 2024
• NVIDIA FLARE: Federated Learning from Simulation to Real-World IEEE Data Eng. Bull., Vol. 46, No. 1, 2023, 2022
• Towards Causal Federated Learning For Enhanced Robustness and Privacy ICLR 2021 Distributed and Private Machine Learning(DPML) Workshop, 2021
• Federated learning with differential privacy and an untrusted aggregator Proceedings of the 10th International Conference on Information Systems Security and Privacy ICISSP - Volume 1, 379-389, 2024, 2023
• Towards Privacy-Guaranteed Label Unlearning in Vertical Federated Learning: Few-Shot Forgetting without Disclosure arXiv, 2024
• How Much Privacy Does Federated Learning with Secure Aggregation Guarantee? arXiv, 2022
• Forgettable Federated Linear Learning with Certified Data Unlearning IEEE Transactions on Neural Networks and Learning Systems, Early Access, pp. 1-10, 2026, 2023
• Federated Learning with GAN-based Data Synthesis for Non-IID Clients arXiv, 2022
• Global Outlier Detection in a Federated Learning Setting with Isolation Forest arXiv, 2024
• Federated Reinforcement Distillation with Proxy Experience Memory arXiv, 2019
• Secure and Efficient Federated Transfer Learning arXiv, 2019
• Fairness, Integrity, and Privacy in a Scalable Blockchain-based Federated Learning System arXiv, 2021
• A Compressive Sensing Approach for Federated Learning over Massive MIMO Communication Systems arXiv, 2020
• From Privacy to Trust in the Agentic Era: A Taxonomy of Challenges in Trustworthy Federated Learning Through the Lens of Trust Report 2.0 Rodríguez-Barroso, et. al. (2026). From Privacy to Trust in the Agentic Era: A Taxonomy of Challenges in Trustworthy Federated Learning Through the Lens of Trust Report 2.0. Information Fusion, 104236, 2025
• HHHFL: Hierarchical Heterogeneous Horizontal Federated Learning for Electroencephalography arXiv, 2019
• LIA: Privacy-Preserving Data Quality Evaluation in Federated Learning Using a Lazy Influence Approximation arXiv, 2022
• Understanding the Resource Cost of Fully Homomorphic Encryption in Quantum Federated Learning arXiv, 2026
• Beyond Static Knowledge Messengers: Towards Adaptive, Fair, and Scalable Federated Learning for Medical AI arXiv, 2025
• Differential Privacy-enabled Federated Learning for Sensitive Health Data arXiv, 2019
• Concealing Sensitive Samples against Gradient Leakage in Federated Learning arXiv, 2022
• Federated Learning Challenges and Opportunities: An Outlook arXiv, 2022
• Feature-based Federated Transfer Learning: Communication Efficiency, Robustness and Privacy arXiv, 2024
• FedFN: Feature Normalization for Alleviating Data Heterogeneity Problem in Federated Learning arXiv, 2023
• Abnormal Client Behavior Detection in Federated Learning arXiv, 2019
• Federated Learning in Distributed Medical Databases: Meta-Analysis of Large-Scale Subcortical Brain Data arXiv, 2018
• Federated Semi-Supervised Learning with Inter-Client Consistency & Disjoint Learning International Conference on Learning Representations (ICLR 2021), International Workshop on Federated Learning for User Privacy and Data Confidentiality in Conjunction with ICML 2020 (FL-ICML'20), 2020
• A Reputation Mechanism Is All You Need: Collaborative Fairness and Adversarial Robustness in Federated Learning arXiv, 2020
• Blockchain-Enabled Federated Learning arXiv, 2025
• Real-World Image Datasets for Federated Learning arXiv, 2019
• FedDiverse: Tackling Data Heterogeneity in Federated Learning with Diversity-Driven Client Selection arXiv, 2025
• Federated Learning with Graph-Based Aggregation for Traffic Forecasting arXiv, 2025
• Privacy in Federated Learning arXiv, 2024
• Aegis: A Trusted, Automatic and Accurate Verification Framework for Vertical Federated Learning arXiv, 2021
• CosSGD: Communication-Efficient Federated Learning with a Simple Cosine-Based Quantization arXiv, 2020