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

Discover how Fourier Analysis breaks down complex time series data into simpler components to identify trends and patterns, despite its limitations in stock forecasting.

Introduction After the WHO prequalified the first vaccine against mpox, we aimed to identify the influence of vaccine ...

Background The relationship of social determinants of health (SDOH), environmental exposures and medical history to lung function trajectories is underexplored. A better understanding of these ...

Introduction Application of artificial intelligence (AI) tools in the healthcare setting gains importance especially in the domain of disease diagnosis. Numerous studies have tried to explore AI in ...

This study proposes an important new approach to analyzing cell-count data, which are often undersampled and cannot be accurately assessed using traditional statistical methods. The case studies ...

Objective To determine how distinct combinations of resistance training prescription (RTx) variables (load, sets and frequency) affect muscle strength and hypertrophy. Data sources MEDLINE, Embase, ...

It would be beneficial to include a few example datasets within the repository. This would allow new users to quickly get started with the Bayesian A/B Test Toolkit without needing to create or find ...

A year ago today, a violent storm struck the coast of the sleepy Sicilian fishing village of Porticello. High winds and dramatic thunder and lightning are not unheard of around this time of year in ...

Objectives The use of cerebral embolic protection (CEP) during transcatheter aortic valve implantation (TAVI) has been studied in several randomised trials. We aimed to perform a systematic review and ...

Abstract: This paper proposes a production decision analysis model based on decision tree and Bayesian optimisation, aiming to optimise the decision-making in the production process of enterprises.

Purpose: Bayesian approaches may improve the efficiency of trials and accelerate decision-making, but reluctance to depart from traditional frequentist statistics may limit their use. Because oncology ...