500 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of CambridgeGB71 papers
- University College LondonGB12 papers
- Newcastle UniversityGB11 papers
- Imperial College LondonGB8 papers
- The Alan Turing InstituteGB7 papers
- Medical Research CouncilGB6 papers
- Sapienza University of RomeIT6 papers
- Novartis (Switzerland)CH5 papers
- Public Health EnglandGB5 papers
- UK Health Security AgencyGB5 papers
- University of OxfordGB5 papers
- Amsterdam University Medical CentersNL4 papers
7 papers · 1 filter
A General Framework for Cutting Feedback within Modularised Bayesian Inference
Yang Liu, Robert J. B. Goudie
Standard Bayesian inference can build models that combine information from various sources, but this inference may not be reliable if components of a model are misspecified. Cut in…
Incorporating Participants' Welfare into Sequential Multiple Assignment Randomized Trials
Xinru Wang, Nina Deliu, Yusuke Narita +1
Dynamic treatment regimes (DTRs) are sequences of decision rules that recommend treatments based on patients' time-varying clinical conditions. The sequential multiple assignment r…
An approximate diffusion process for environmental stochasticity in infectious disease transmission modelling
Sanmitra Ghosh, Paul J. Birrell, Daniela De Angelis
Modelling the transmission dynamics of an infectious disease is a complex task. Not only it is difficult to accurately model the inherent non-stationarity and heterogeneity of tran…
Bayesian sample size determination in basket trials borrowing information between subsets
Haiyan Zheng, Michael J. Grayling, Pavel Mozgunov +2
Basket trials are increasingly used for the simultaneous evaluation of a new treatment in various patient subgroups under one overarching protocol. We propose a Bayesian approach t…
Some performance considerations when using multi-armed bandit algorithms in the presence of missing data
Xijin Chen, Kim May Lee, Sofia S. Villar +1
When comparing the performance of multi-armed bandit algorithms, the potential impact of missing data is often overlooked. In practice, it also affects their implementation where t…
A comparison of two frameworks for multi-state modelling, applied to outcomes after hospital admissions with COVID-19
Christopher Jackson, Brian Tom, Peter Kirwan +5
We compare two multi-state modelling frameworks that can be used to represent dates of events following hospital admission for people infected during an epidemic. The methods are a…
Reinforcement Learning in Modern Biostatistics: Constructing Optimal Adaptive Interventions
Nina Deliu, Joseph Jay Williams, Bibhas Chakraborty
In recent years, reinforcement learning (RL) has acquired a prominent position in health-related sequential decision-making problems, gaining traction as a valuable tool for delive…