Many antineoplastics are designed to target upregulated genes, but quantifying upregulation in a single patient sample requires an appropriate set of samples for comparison. In cancer, the most ...

Bayesian Additive Regression Trees (BART) is a nonparametric ensemble method that models complex relationships by summing a collection of decision trees, each operating as a weak learner. The Bayesian ...

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

Artificial intelligence can solve problems at remarkable speed, but it's the people developing the algorithms who are truly driving discovery. At The University of Texas at Arlington, data scientists ...

In a world of uncertainty and shifting narratives, this post proposes a new model for investing: Bayesian edge investing. Unlike modern portfolio theory, which assumes equilibrium and perfect ...

Association of intestinal exfoliome and Prevotellaceae with toxicity and clinical outcome during immune-checkpoint blockade. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This ...

FDA proposes framework clinical trial designs to guide Bayesian methods, improving efficiency in drug development for rare and pediatric conditions.

This is a preview. Log in through your library . Abstract We propose a novel Bayesian hierarchical model for brain imaging data that unifies voxel-level (the most localized unit of measure) and region ...

We adapt a semi-Bayesian hierarchical modeling framework to jointly characterize the space–time variability of seasonal precipitation totals and precipitation extremes across the Northern Great Plains ...