The clinical trial ecosystem is entering a phase of consolidation and reinvention driven by the collapse of boundaries between functions, data, and even companies themselves.

Explainable AI (XAI) exists to close this gap. It is not just a trend or an afterthought; XAI is an essential product capability required for responsibly scaling AI. Without it, AI remains a powerful ...

Healthcare is a complex socio-technical system, not a purely technical environment. Clinical decisions are shaped not only by ...

Artificial intelligence (AI) is increasingly used to analyze medical images, materials data and scientific measurements, but ...

Training artificial intelligence models is costly. Researchers estimate that training costs for the largest frontier models ...

In Kenya, recent initiatives to modernise border processing are designed to reduce clearance times and make trade reporting ...

AI’s predictive power is transformative, but its lack of explainability, contextual understanding, and causal reasoning ...

Here's a sharper definition of what AI SOC platforms can do today and what they cannot, and how to evaluate these platforms ...

CARE-ACE supports autonomy through bounded agentic reasoning, in which diagnostic, prognostic, planning, and risk-assessment ...

Key data and analytics trends in 2026 include decision intelligence, real-time analytics, semantic layers, platform ...

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...