7 citations · 10 across the 6 of their papers we have counts for
8 papers
Calibration of answer probabilities in verbal autopsies: Working Paper
James Liley, Nathan Higgins, Eilidh Cowan
We consider the problem of calibrating a posterior estimator of a categorical latent variable given a fixed-length ternary string using only unlabelled observations and without a s…
AMUSE: Adaptive Model Updating using a Simulated Environment
Louis Chislett, Catalina A. Vallejos, Timothy I. Cannings +1
Prediction models frequently face the challenge of concept drift, in which the underlying data distribution changes over time, weakening performance. Examples can include models wh…
Ethical considerations of use of hold-out sets in clinical prediction model management
Louis Chislett, Louis JM Aslett, Alisha R Davies +2
Clinical prediction models are statistical or machine learning models used to quantify the risk of a certain health outcome using patient data. These can then inform potential inte…
GRAIMATTER Green Paper: Recommendations for disclosure control of trained Machine Learning (ML) models from Trusted Research Environments (TREs)
Emily Jefferson, James Liley, Maeve Malone +16
TREs are widely, and increasingly used to support statistical analysis of sensitive data across a range of sectors (e.g., health, police, tax and education) as they enable secure a…
Holdouts set for safe predictive model updating
Sami Haidar-Wehbe, Samuel R Emerson, Louis J M Aslett +1
Predictive risk scores for adverse outcomes are increasingly crucial in guiding health interventions. Such scores may need to be periodically updated due to change in the distribut…
Stacking interventions for equitable outcomes
James Liley
Predictive risk scores estimating probabilities for a binary outcome on the basis of observed covariates are common across the sciences. They are frequently developed with the inte…
Model updating after interventions paradoxically introduces bias
James Liley, Samuel R Emerson, Bilal A Mateen +3
Machine learning is increasingly being used to generate prediction models for use in a number of real-world settings, from credit risk assessment to clinical decision support. Rece…
Combining controls can improve power in two-stage association studies
James Liley
High dimensional case control studies are ubiquitous in the biological sciences, particularly genomics. To maximise power while constraining cost and to minimise type-1 error rates…