A new Bayesian framework called PIML combines machine learning analysis of electrical impedance signals with clinical prior ...

Researchers at The University of Texas at Arlington have developed a new computational tool that helps scientists pinpoint proteins known as transcriptional regulators that control how genes turn on ...

Researchers must often choose between Bayesian or neural network models of behavior, two paradigms with complementary strengths and weaknesses. An ideal paradigm would facilitate testing many kinds of ...

Researchers have introduced a statistical model designed to predict disease from microbiome data pooled across many studies, ...

Ed Ahearne combined automation , machine learning and Bayesian optimization to speed up method development for siRNA medicines. At ISC 2016, Edward Ahearne of AstraZeneca’s Pharmaceutical Sciences - ...

When a computer scientist publishes genetics papers, you might think it would raise colleagues’ eyebrows. But Daphne Koller’s research using a once obscure branch of probability theory called Bayesian ...