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A Recommendation and Risk Classification System for Connecting Rough Sleepers to Essential Outreach Services

Rough sleeping is a chronic problem faced by some of the most disadvantaged people in modern society. This paper describes work carried out in partnership with Homeless Link, a UK-based charity, in developing a data-driven approach to assess the …

Digital Health Management During and Beyond the COVID-19 Pandemic: Opportunities, Barriers, and Recommendations

During the coronavirus disease (COVID-19) crisis, digital technologies have become a major route for accessing remote care. Therefore, the need to ensure that these tools are safe and effective has never been greater. We raise five calls to action to …

Machine learning and artificial intelligence research for patient benefit: 20 critical questions on transparency, replicability, ethics, and effectiveness

A geotemporal survey of hospital bed saturation across England during the first wave of the COVID-19 Pandemic

Diabetes and COVID-19 Related Mortality in the Critical Care Setting: A Real-Time National Cohort Study in England

Background: The importance of diabetes as a prognostic factor in people admitted to hospital critical care with COVID-19 is poorly understood and has not been quantified. Methods: We used a real-time national database (COVID-19 Hospitalisation in …

Multi-level Monte Carlo methods for the approximation of invariant measures of stochastic differential equations

We develop a framework that allows the use of the multi-level Monte Carlo (MLMC) methodology (Giles in Acta Numer. 24: 259--328, 2015. https://doi. org/10.1017/ S096249291500001X) to calculate expectations with respect to the invariant measure of an …

Measuring sample quality with diffusions

Project Euclid - mathematics and statistics online

Design choices for productive, secure, data-intensive research at scale in the cloud

We present a policy and process framework for secure environments for productive data science research projects at scale, by combining prevailing data security threat and risk profiles into five sensitivity tiers, and, at each tier, specifying …

Unbiased Monte Carlo: Posterior estimation for intractable/infinite-dimensional models

Project Euclid - mathematics and statistics online

The Bouncy Particle Sampler: A Nonreversible Rejection-Free Markov Chain Monte Carlo Method

ABSTRACTMany Markov chain Monte Carlo techniques currently available rely on discrete-time reversible Markov processes whose transition kernels are variations of the Metropolis?Hastings algorithm. We explore and generalize an alternative scheme …