Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Abstract: Conventional neural network-based machine learning algorithms often encounter difficulties in data-limited scenarios or where interpretability is critical. Conversely, Bayesian ...

A team of international physicists has brought Bayes’ centuries-old probability rule into the quantum world. By applying the “principle of minimum change” — updating beliefs as little as possible ...

Abstract: Naïve Bayesian inference enables classification or prediction of an event given observations of potentially contradictory evidences, and is particularly intriguing in power-limited contexts ...

Department of Engineering, University of Cambridge, Cambridge CB2 1CB2 1PZ, U.K.

Stable distributions are well-known for their desirable properties and can effectively fit data with heavy tail. However, due to the lack of an explicit probability density function and finite second ...

Objectives: We aimed to clarify the influence of facial expressions on providing early recognition and diagnosis of Parkinson’s disease (PD). Methods: We included 18 people with PD and 18 controls.

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, ...