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

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

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

The FDA’s new draft guidance on Bayesian methodology signals a shift toward more flexible, data-driven clinical trial designs, enabling sponsors to use prior data and adaptive approaches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

Expansion of antiretroviral therapy in Uganda sharply reduced orphanhood incidence, especially among adolescents, but ...

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

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

One of the most difficult challenges in payment card fraud detection is extreme class imbalance. Fraudulent transactions ...

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

Background The relationship of social determinants of health (SDOH), environmental exposures and medical history to lung function trajectories is underexplored. A better understanding of these ...

Researchers have developed a hybrid CFD-neural network model for predicting TAIs in hydrogen-fueled turbines, improving ...

The following information was released by the Federal Reserve Bank of Atlanta:. In preparation for FOMC meetings, policymakers have the Fed Board staff projection of this "advance" estimate at their ...