4 papers
A Causal Framework for Mitigating Data Shifts in Healthcare
Kurt Butler, Stephanie Riley, Damian Machlanski +13
Developing predictive models that perform reliably across diverse patient populations and heterogeneous environments is a core aim of medical research. However, generalization is o…
A flexible approach to sequential prediction under intervention
Matthew Sperrin, Bowen Jiang, Joyce Huang +2
We propose a causal predictive framework for estimating risk under preventative interventions. The Unexposed Mediator Model maintains mediators that are also predictors at their un…
Prediction of Survival Outcomes under Clinical Presence Shift: A Joint Neural Network Architecture
Vincent Jeanselme, Glen Martin, Matthew Sperrin +3
Electronic health records arise from the complex interaction between patients and the healthcare system. This observation process of interactions, referred to as clinical presence,…
The continuous net benefit: Assessing the clinical utility of prediction models when informing a continuum of decisions
Jose Benitez-Aurioles, Laure Wynants, Niels Peek +3
Clinical prognostic models help inform decision-making by estimating a patient's risk of experiencing an outcome in the future. The net benefit is increasingly being used to assess…