Nature

Bayesian statistics and modelling

Bayesian statistics is an approach to data analysis based on Bayes’ theorem, where available knowledge about parameters in a statistical model is updated with the information in observed data. The ...
Diginomica

Can Bayesian Networks provide answers when Machine Learning comes up short? It's a question of probabilities

Machine Learning gets all the marketing hype, but are we overlooking Bayesian Networks? Here's a deeper look at why "Bayes Nets" are underrated - especially when it comes to addressing probability and ...
Pharm Exec

Bringing the Bayesian Method to Clinical Trials: Q&A with Dr. Stacy Lindborg

Bayesian trials formally integrate prior evidence with accruing data to yield posterior probabilities, supporting interim learning, adaptive modifications, and direct predictive futility/efficacy ...
Nature

Bayesian network-based over-sampling method (BOSME) with application to indirect cost-sensitive learning

Traditional supervised learning algorithms do not satisfactorily solve the classification problem on imbalanced data sets, since they tend to assign the majority class, to the detriment of the ...
RAPS

Industry asks FDA to affirm Bayesian methods guidance applies broadly to drugs

Industry groups and drugmakers want the US Food and Drug Administration (FDA) to explicitly clarify that Bayesian statistical methods can be used for products beyond those intended for children and ...
The Conversation

Bayes’ Theorem: the maths tool we probably use every day, but what is it?

Our world view and resultant actions are often driven by a simple theorem, devised in secret more than 150 years ago by a quiet English mathematician and theologian, Thomas Bayes, and only published ...