Why today’s AI systems struggle with consistency, and how emerging world models aim to give machines a steady grasp of space ...

Researchers risk fire, explosion or poisoning by allowing AI to design experiments, warn scientists. Some 19 different AI ...

The FDA’s new draft guidance on Bayesian methodology signals a shift toward more flexible, data-driven clinical trial designs, enabling sponsors to use prior data and adaptive approaches to improve ...

Rainfall prediction has advanced rapidly with the adoption of machine learning, but most models remain optimized for overall ...

Discover how credibility theory helps actuaries use historical data to estimate risks and set insurance premiums; learn how ...

These open-source MMM tools solve different measurement problems, from budget optimization to forecasting and preprocessing.

Researchers have employed Bayesian neural network approaches to evaluate the distributions of independent and cumulative ...

The ROAR trial tested the hypothesis that returning familial hypercholesterolemia-associated genetic results leads to ...

How modern mathematics helps policymakers and insurers connect the dots of the country’s fragmented demographic data ...

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

Life on the windswept plains of what is now central Ukraine offered little mercy around 18,000 years ago. Trees were scarce.

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...