Detecting concealed explosives and chemical threats constitutes a critical challenge in global security, yet current ...

Deep learning techniques can enhance diagnosis of Meniere disease (MD) and severity grading, according to a study published ...

Radiologist demand grew 17% despite AI permeating imaging—the blueprint for agentic AI is expansion, not replacement.

AI-based security detection automates the analysis of large, complex data sets to uncover threats in real time. These systems not only flag potential risks but can also trigger automated response ...

The numbers tell a stark story: $1.42 billion lost across 149 documented incidents in 2024 due to smart contract vulnerabilities, with access control ...

The cybersecurity landscape in 2026 will be dominated by AI-embedded risks, autonomous attacks, and supply chain ...

In this context, red teaming is no longer a niche exercise. It is the backbone for building secure, compliant, and ...

DiaCardia, a novel artificial intelligence model that can accurately identify individuals with prediabetes using either 12-lead or single-lead electrocardiogram (ECG) data, has been recently developed ...

Researchers in the US developed bipedal robots with a new design, the HybridLeg platform, ...

Study in a Sentence: Cedars-Sinai researchers are developing KronosRx, an artificial intelligence-powered platform that uses human-derived organoids and deep-learning models to forecast adverse drug ...

A robot can walk better, stay balanced, and learn for longer without falling. Its smart design makes humanoid robots stronger ...

If animals clocked in as we do, half of us would already be late. Many of them run on tighter routines than humans ever ...