Author

B. van Calster

3 papers indexed here

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Open access Aug 2026

Recent criteria and simple rules agreed often on required sample size for developed clinical prediction models.

OBJECTIVE Adequate sample size is essential to the development of new prediction models with binary outcomes. We aim to relate recent approaches to traditional rules of thumb ('simple rules') and assess agreement and differences in judging adequacy of sample size for developed prediction models. STUDY DESIGN AND SETT...

E. Steyerberg, Tobias Hackmann, B. van Calster et al. · Journal of Clinical Epidemio... · 0 citations

#machine learning Preprint Sep 2026

Optimizing for the decision not the prediction: an exploration of Smooth Net Benefit as a training objective

The results do not support $\sigma$NB as a general replacement for NLL training, but support further investigation of decision-focused objectives in settings where conventional likelihood-based training may not adequately capture decision-relevant structure.

Koen M. F. Gorgels, L. Barreñada, M. van Smeden et al. · 0 citations

#artificial intelligence Preprint Aug 2026

Collapsibility of Performance Metrics in Clinical Predictive AI

The AUC is shown to be non-collapsible because it decomposes into within- and cross-group AUC terms when subpopulations coexist, such that its overall value may fall outside the range of subgroup specific AUCs.

João Matos, B. van Calster, Richard D. Riley et al. · 0 citations