4 citations · 5 across the 5 of their papers we have counts for
3 papers · 1 filter
Optimizing for the decision not the prediction: an exploration of Smooth Net Benefit as a training objective
Koen M. F. Gorgels, Lasai Barreñada, Maarten van Smeden +3
Objective Prediction models are commonly trained using objectives such as Bernoulli negative log-likelihood (NLL), although downstream clinical decisions may depend on specific ris…
Collapsibility of Performance Metrics in Clinical Predictive AI
João Matos, Ben Van Calster, Richard D. Riley +2
Background: Population level assessments of predictive artificial intelligence (AI) can conceal performance disparities across subgroups. Fairness evaluations commonly rely on perf…
Comparison of static and dynamic random forests models for EHR data in the presence of competing risks: predicting central line-associated bloodstream infection
Elena Albu, Shan Gao, Pieter Stijnen +6
Prognostic outcomes related to hospital admissions typically do not suffer from censoring, and can be modeled either categorically or as time-to-event. Competing events are common…