activity
20102025
most citedClinical Prediction Models to Predict the Risk of Multiple Binary Outcomes: a comparison of approaches

35 citations · 104 across the 15 of their papers we have counts for

collaborators

15 papers

stat.ME2025

Compatibility of Missing Data Handling Methods across the Stages of Producing Clinical Prediction Models

Antonia Tsvetanova, Matthew Sperrin, David A. Jenkins +7

Missing data is a challenge when developing, validating and deploying clinical prediction models (CPMs). Traditionally, decisions concerning missing data handling during CPM develo…

stat.ME2024★ 1 cited

The risks of risk assessment: causal blind spots when using prediction models for treatment decisions

Nan van Geloven, Ruth H Keogh, Wouter van Amsterdam +12

Clinicians increasingly rely on prediction models to guide treatment choices. Most prediction models, however, are developed using observational data that include some patients who…

stat.ME2023★ 4 cited

Risk-based decision making: estimands for sequential prediction under interventions

Kim Luijken, Paweł Morzywołek, Wouter van Amsterdam +14

Prediction models are used amongst others to inform medical decisions on interventions. Typically, individuals with high risks of adverse outcomes are advised to undergo an interve…

stat.ME2023

Calibration plots for multistate risk predictions models: an overview and simulation comparing novel approaches

Alexander Pate, Matthew Sperrin, Richard D. Riley +9

Introduction. There is currently no guidance on how to assess the calibration of multistate models used for risk prediction. We introduce several techniques that can be used to pro…

stat.ME2022

Imputation and Missing Indicators for handling missing data in the development and implementation of clinical prediction models: a simulation study

Rose Sisk, Matthew Sperrin, Niels Peek +2

Background: Existing guidelines for handling missing data are generally not consistent with the goals of prediction modelling, where missing data can occur at any stage of the mode…

cs.LG2022★ 2 cited

DeepJoint: Robust Survival Modelling Under Clinical Presence Shift

Vincent Jeanselme, Glen Martin, Niels Peek +3

Observational data in medicine arise as a result of the complex interaction between patients and the healthcare system. The sampling process is often highly irregular and itself co…