11 citations · 20 across the 5 of their papers we have counts for
5 papers
The harms of class imbalance corrections for machine learning based prediction models: a simulation study
Alex Carriero, Kim Luijken, Anne de Hond +3
Risk prediction models are increasingly used in healthcare to aid in clinical decision making. In most clinical contexts, model calibration (i.e., assessing the reliability of risk…
Cross-institution text mining to uncover clinical associations: a case study relating social factors and code status in intensive care medicine
Madhumita Sushil, Atul J. Butte, Ewoud Schuit +2
Objective: Text mining of clinical notes embedded in electronic medical records is increasingly used to extract patient characteristics otherwise not or only partly available, to a…
Minimum Sample Size for Developing a Multivariable Prediction Model using Multinomial Logistic Regression
Alexander Pate, Richard D Riley, Gary S Collins +4
Multinomial logistic regression models allow one to predict the risk of a categorical outcome with more than 2 categories. When developing such a model, researchers should ensure t…
The harm of class imbalance corrections for risk prediction models: illustration and simulation using logistic regression
Ruben van den Goorbergh, Maarten van Smeden, Dirk Timmerman +1
Methods to correct class imbalance, i.e. imbalance between the frequency of outcome events and non-events, are receiving increasing interest for developing prediction models. We ex…
Sensitivity analysis for bias due to a misclassfied confounding variable in marginal structural models
Linda Nab, Rolf H. H. Groenwold, Maarten van Smeden +1
In observational research treatment effects, the average treatment effect (ATE) estimator may be biased if a confounding variable is misclassified. We discuss the impact of classif…