In this video interview, David Morton, PhD, director of biostatistics at Certara, explores the practical challenges of implementing Bayesian designs, including the need for simulation, ...
Bayesian statistical models use prior data to update the probability of a hypothesis as new evidence emerges. Image credit: PeopleImages / Shutterstock.com Bayesian statistical models could help ...
The FDA’s new draft guidance on Bayesian methods in clinical trials has been hailed by some as a breakthrough that could speed drug development. But statisticians and researchers are divided on ...
Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...
Marty Makary was appointed commissioner of the Food and Drug Administration (FDA) in 2025. The prominent surgeon, medical researcher, bestselling author, and critic of the medical ...
In recent years, something unexpected has been happening in artificial intelligence. Modern AI appears to be breaking a rule that statisticians have preached for nearly a century: Keep models in a ...
Invasive species are among the leading threats to forests across North America. Among them, the spongy moth and Douglas-fir tussock moth are responsible for extensive damage to forests from coast to ...
ABSTRACT: This paper investigates the application of machine learning techniques to optimize complex spray-drying operations in manufacturing environments. Using a mixed-methods approach that combines ...
Bayesian methods for inference and prediction have become widespread in the social sciences (and beyond). Over the last decades, applied Bayesian modeling has evolved from a niche methodology with ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results