The FDA has released draft guidance on how sponsors can use Bayesian models for clinical trials.

As rare disease trials face persistent feasibility challenges, Bayesian designs are gaining momentum by enabling more ...

A new study introduces a global probabilistic forecasting model that predicts when and where ionospheric disturbances—measured by the Rate of total electron content (TEC) Index (ROTI)—are likely to ...

This study provides important insights into how working memory shapes perceptual decisions, using a dual-task design, continuous mouse tracking, and hierarchical Bayesian modeling. By dissociating ...

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We review Bayesian and Bayesian decision theoretic approaches to subgroup analysis and applications to subgroup-based adaptive clinical trial designs. Subgroup analysis refers to inference about ...

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, ...

In studying structural inter-connections in the human brain, it is common to first estimate fiber bundles connecting different regions relying on diffusion MRI. These fiber bundles act as highways for ...

Dr. James McCaffrey of Microsoft Research shows how to predict a person's sex based on their job type, eye color and country of residence. Naive Bayes classification is a classical machine learning ...