Security Boulevard

AI-Driven Anomaly Detection for MCP Security.

Explore how AI-driven anomaly detection enhances the security of Model Context Protocol (MCP) deployments, protecting AI infrastructure from evolving threats with real-time insights.
Devdiscourse

Big data fraud detection faces a reckoning over AI transparency

Traditional rule-based systems, once sufficient for detecting simple patterns of fraud, have been overwhelmed by the scale, ...
Security Boulevard

How powerful are current AI solutions in detecting NHIDR

What Are Non-Human Identities (NHIs), and Why Are They Crucial in Today’s Cloud Environment? Where data breaches and cyber threats are escalating, how do organizations secure the growing ...
News-Medical.Net on MSN

Automated system improves deep learning accuracy in chest radiography analysis

Researchers at Osaka Metropolitan University have discovered a practical way to detect and fix common labeling errors in ...

Automatic label checking: The missing step in making medical AI reliable

Researchers at Osaka Metropolitan University have discovered a practical way to detect and fix common labeling errors in ...
Scientific Research Publishing

De-Risking Returns: How AI Can Reinvent Big Tech’s China-Tied Reverse Supply Chains ()

Reverse Logistics, Artificial Intelligence, Circular Economy, Supply Chain Management, Sustainability, Machine Learning Share and Cite: Waditwar, P. (2026) De-Risking Returns: How AI Can Reinvent Big ...
BMJ Open

Using virtual twin-based AI models to detect atrial fibrillation and improve stroke outcomes [TAILOR]: a multicentre prospective cohort study

Introduction Atrial fibrillation (AF) is the leading cause of cardioembolic stroke and is associated with increased stroke severity and fatality. Early identification of AF is essential for adequate ...