federated learning

Artificial Intelligence–Driven Digital Twins, Multi-Omics and Precision Hepatitis Care: Emerging Innovations, Challenges, and Future Perspectives

Due to persistent diagnostic delays, varied disease progression, and unpredictable therapy responses, viral hepatitis remains a major worldwide health concern despite advances in antiviral medication and vaccine. Precision hepatology is a viable strategy for overcoming these limitations through tailored, data-driven cl...

Artificial Intelligence–Driven Digital Twins, Multi-Omics and Precision Hepatitis Care: Emerging Innovations, Challenges, and Future Perspectives

Due to persistent diagnostic delays, varied disease progression, and unpredictable therapy responses, viral hepatitis remains a major worldwide health concern despite advances in antiviral medication and vaccine. Precision hepatology is a viable strategy for overcoming these limitations through tailored, data-driven cl...

Next-Generation Deep Learning: A Comprehensive Survey on Explainable, Efficient, Privacy-Preserving and Multimodal Artificial Intelligence

The continuous evolution of deep learning has significantly expanded the capabilities of artificial intelligence, enabling intelligent systems to solve increasingly complex problems across healthcare, computer vision, natural language processing, cybersecurity, finance, autonomous systems, and smart environments.Beginn...

FOIN: A Federated Multi-Organoid Intelligence Architecture using Combinatorial Graph Modelling

Open research challenges and future directions for multimodal healthcare security

The swift advancement of multimodal artificial intelligence (AI) has changed the face of integration of diverse data types, such as medical images, texts, biosignals, genomics, wearables, and clinical data in the field of medicine. However, the deployment of reliable, secure, and scaled multimodal healthcare systems is...

AI-driven cybersecurity for industrial internet of things: architectures, challenges, datasets, and future research directions

This review critically analyzes the cybersecurity research published over the past few years on cyber threats across the various layers of the IIoT architecture, publicly available cybersecurity datasets, evaluation practices, and AI-based intrusion detection methods to provide a pathway toward resilient, adaptive, and...

Edge AI: Embedded Intelligence, a Review on Hardware and Applications

A unified analytical framework is introduced that models inference latency, bandwidth, energy, computational complexity, throughput, and model compression, and is used to compare cloud versus edge execution.

Privacy-preserving federated learning AdaBoost via knowledge distillation

Decomposed tensorized graph learning with representation-induced view recovery for federated incomplete multi-view clustering

Enhancing security and early detection of hypoxic-ischemic encephalopathy in neonates by using meta federated learning with enhanced Swin transformer

Federated learning ownership verification with fixed length watermarks using hash-based message authentication code

Research on intrusion detection of smart substation power grid based on deep Q-network and federated learning