In genetic analysis, there are often competing explanations for the same data. Sophisticated mathematical models have been developed that can encapsulate these problems in terms of parameters that ...

Introduction: Bayesian data mining methods have been used to evaluate drug safety signals from adverse event reporting systems and allow for evaluation of multiple endpoints that are not prespecified.

This illustration gives a sense of how characters from alphabets around the world were replicated through human vs. machine learning. (Credit: Danqing Wang) Researchers say they’ve developed an ...

This article was published in Scientific American’s former blog network and reflects the views of the author, not necessarily those of Scientific American I’m not sure when I first heard of Bayes’ ...

A deep learning framework enhances medical image recognition by optimizing RNN architectures with LSTM, GRU, multimodal fusion, and CNN ...

Over the years, many writers have implied that statistics can provide almost any result that is convenient at the time. Of course, honest practitioners use statistics in an attempt to quantify the ...

Several criteria for Bayesian sample size determination have recently been proposed. Criteria based on highest posterior density (HPD) intervals from the exact posterior distribution in general lead ...

Measuring Tumor Epichaperome Expression Using [124I] PU-H71 Positron Emission Tomography as a Biomarker of Response for PU-H71 Plus Nab-Paclitaxel in HER2-Negative Metastatic Breast Cancer For ...

Notice that the best design was found in three tries out of ten. It may be a good idea to repeat the search with more tries (see the ITER= option.) You can use the ALIASING option of the GLM procedure ...