Learn how prior probability informs economic theory and decision-making in Bayesian statistics. Understand its role before collecting new data.

Objectives Delays in cancer diagnosis for patients with non-specific symptoms (NSSs) lead to poorer outcomes. Rapid Diagnostic Clinics (RDCs) expedite care, but most NSS patients do not have cancer, ...

This paper discusses the Bayesian approach as an alternative to the classical analysis of nonlinear models for growth curve data in Japanese quail. A Bayesian nonlinear modeling method is introduced ...

Abstract: Blockchain has found many uses beyond cryptocurrency trading. However, this technology faces the challenge of low transactions per second (TPS), which hinders it from competing at scale with ...

Paper aims This paper presents a comparison of the performances of the Bayesian additive regression trees (BART), Random Forest (RF) and the logistic regression model (LRM) for the development of ...

ABSTRACT: In order to solve the problem of chronic heart failure risk prediction in the elderly, a logistic regression modeling framework with Bayesian method was proposed, aiming to solve the problem ...

ABSTRACT: In order to solve the problem of chronic heart failure risk prediction in the elderly, a logistic regression modeling framework with Bayesian method was proposed, aiming to solve the problem ...

Empowered by technological progress, sports teams and bookmakers strive to understand relationships between player and team activity and match outcomes. For this purpose, the probability of an event ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

The body of the vessel’s cook was recovered while divers searched the hull of the Bayesian for passengers, including the tech entrepreneur Mike Lynch. By Elisabetta Povoledo Deep-sea divers with Italy ...