Bayes' Theorem: What It Is, Formula, and Examples

Bayes' theorem is a statistical formula used to calculate conditional probability. Learn how it works, how to calculate it ...
Cochrane

Bayesian Meta-Analysis: making it accessible for everyone!

This webinar introduced healthcare researchers to Bayesian meta-analysis methods, challenging the perception that these methods are inaccessible to non-statistical researchers. The session ...
eLife

Virtual Brain Inference (VBI): A flexible and integrative toolkit for efficient probabilistic inference on virtual brain models

Not revised: This Reviewed Preprint includes the authors’ original preprint (without revision), an eLife assessment, public reviews, and a provisional response from the authors. This work provides a ...
IEEE

RESPLE: Recursive Spline Estimation for LiDAR-Based Odometry

Abstract: We present a novel recursive Bayesian estimation framework using B-splines for continuous-time 6-DoF dynamic motion estimation. The state vector consists of a recurrent set of position ...
Frontiers

A guide to bayesian networks software for structure and parameter learning, with a focus on causal discovery tools

1 Minutia.AI Pte. Ltd., Singapore, Singapore 2 Department of Informatics, Systems and Communication, University of Milano-Bicocca, Milano, Italy A representation of the cause-effect mechanism is ...
IEEE

Interacting Multiple Model-Based Moving Horizon Estimation With Variational Bayesian

Abstract: Moving Horizon Estimation (MHE) is widely used for state estimation due to its ability to effectively incorporate historical information. As a single-model approach, its accuracy depends not ...
SciELO

AN EFFICIENT COUNT DATA MODEL: PROPERTIES, ACTUARIAL MEASURES, BAYESIAN ESTIMATION, REGRESSION MODEL, AND APPLICATIONS TO HEALTH CARE DATA

Based on the compounding mechanism, a unique discrete probability distribution is investigated in this paper. The Poisson distribution is mixed with a lifetime model called as the Fav-Jerry model. The ...
Scientific Research Publishing

Bayesian Interval Estimation of the Prevalence Rate Using Pool Testing Strategy with Retesting ()

Mathematics Department, Egerton University, Njoro Nakuru, Kenya. Bayesian techniques have been applied in many epidemiological settings, such as disease monitoring, outbreak simulation, and prevalence ...
ascopubs.org

Improving clinical trial interpretability and efficiency: A Bayesian re-analysis of individual patient outcomes from 230 phase III oncology trials.

Benefit of adding Cureety remote patient monitoring (RPM) to usual care during injectable anticancer treatment: The OPTIMACURE multicentric French prospective randomized study. This is an ASCO Meeting ...
ascopubs.org

Clinical outcomes of chemotherapy with or without intravesical BCG in NMIBC patients: A Bayesian network meta-analysis.

This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does not include a full text component.