Multimodal federated learning: A survey
Federated learning (FL), which provides a collaborative training scheme for distributed data
sources with privacy concerns, has become a burgeoning and attractive research area. Most …
sources with privacy concerns, has become a burgeoning and attractive research area. Most …
[HTML][HTML] Hierarchical pretraining on multimodal electronic health records
Pretraining has proven to be a powerful technique in natural language processing (NLP),
exhibiting remarkable success in various NLP downstream tasks. However, in the medical …
exhibiting remarkable success in various NLP downstream tasks. However, in the medical …
Knowledge-enhanced semi-supervised federated learning for aggregating heterogeneous lightweight clients in iot
Federated learning (FL) enables multiple clients to train models collaboratively without
sharing local data, which has achieved promising results in different areas, including the …
sharing local data, which has achieved promising results in different areas, including the …
[PDF][PDF] Backdoor threats from compromised foundation models to federated learning
Federated learning (FL) represents a novel paradigm to machine learning, addressing
critical issues related to data privacy and security, yet suffering from data insufficiency and …
critical issues related to data privacy and security, yet suffering from data insufficiency and …
[PDF][PDF] Federated learning for rare disease detection: a survey
The detection of rare diseases utilizing advanced artificial intelligence (AI) techniques has
garnered considerable attention in recent years. Numerous approaches have been …
garnered considerable attention in recent years. Numerous approaches have been …
Recent Advances in Predictive Modeling with Electronic Health Records
The development of electronic health records (EHR) systems has enabled the collection of a
vast amount of digitized patient data. However, utilizing EHR data for predictive modeling …
vast amount of digitized patient data. However, utilizing EHR data for predictive modeling …
Rethinking Personalized Federated Learning with Clustering-Based Dynamic Graph Propagation
Most existing personalized federated learning approaches are based on intricate designs,
which often require complex implementation and tuning. In order to address this limitation …
which often require complex implementation and tuning. In order to address this limitation …
Vulnerabilities of foundation model integrated federated learning under adversarial threats
Federated Learning (FL) addresses critical issues in machine learning related to data
privacy and security, yet suffering from data insufficiency and imbalance under certain …
privacy and security, yet suffering from data insufficiency and imbalance under certain …
FEDMEKI: A Benchmark for Scaling Medical Foundation Models via Federated Knowledge Injection
This study introduces the Federated Medical Knowledge Injection (FEDMEKI) platform, a
new benchmark designed to address the unique challenges of integrating medical …
new benchmark designed to address the unique challenges of integrating medical …
Leveraging Foundation Models for Multi-modal Federated Learning with Incomplete Modality
Federated learning (FL) has obtained tremendous progress in providing collaborative
training solutions for distributed data silos with privacy guarantees. However, few existing …
training solutions for distributed data silos with privacy guarantees. However, few existing …