AI agents help businesses stop guessing — linking predictions to actions so teams can move from “what might happen” to ...

Read more about AI-driven learning analytics struggle to deliver measurable gains in higher education on Devdiscourse ...

Researchers have developed a new machine-learning-assisted approach to optimize micro-electro-discharge machining (µ-EDM) of ...

According to A Survey of AI-Enabled Predictive Maintenance for Railway Infrastructure: Models, Data Sources, and Research Challenges, published in Sensors, AI-based predictive maintenance systems ...

Interpretable AI model could offer new insights into why medicines cause certain side effects, helping to improve future drug safety predictions.

Regulatory requirements are fueling the growth of preventive AI gambling measures. In Ontario, the AGCO has required ...

Real-world data (RWD) is transforming clinical research, augmenting existing randomized controlled trial (RCT) data to de-risk studies and improve generalizability. With regulators setting clearer ...

Companies investing in AI initiatives succeed by focusing on real business value, strong data readiness, and securing employee buy in across teams.

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

Data readiness remains a major challenge, particularly when dealing with legacy systems and decades of unstructured records ...

For the first time, heavy-duty trucking fleet managers and technicians can actually partner with intelligent machines to ...

Faraz Ahmad, MD, and Marie-Noelle Langan, MD, discuss the role of artificial intelligence (AI) for cardiac care within healthcare systems.