In our latest work, we show that risk estimates for patients are HUGELY uncertain due to model, data, and population uncertainty. Even for well performing models (c statistic, calibration, utility) based on large N.
@laure_wynants @ESteyerberg @lasaibarrenada.bsky.social

arxiv.org/abs/2506.17141

What a great day yesterday! 🎉 Dr. Shan Gao and Dr. Elena Albu successfully defended their PhDs on the dynamic prediction of CLABSI using EHR data. A huge milestone after four years of dedicated research!

PROBAST+AI is out! A risk of bias tool for prediction models developed using any kind of analytical approach (stats/ml/ai/ds)

Really proud of this collaboration with many prediction model experts around the world

www.bmj.com/content/388/...

I will be presenting our recent work on individual risk estimation uncertainty at ENAR in New Orleans. Come say hi!

Work with @benvancalster.bsky.social @laurewynants.bsky.social #DoranneThomassen #EwoutSteyerberg

Are you a statistician or health-economist who wants to develop new methods and who is interested in evaluating the role of diagnostic & prognostic prediction models and AI? We have an opening for a PhD position at Maastricht University!

www.academictransfer.com/nl/jobs/3503...

NEW PREPRINT 📊: We propose 3 methods to obtain flexible calibration plots while accounting for clustering:

1. Clustered Group Calibration (CG-C)
2. Two-Stage Meta-Analysis Calibration (2MA-C)
3. Mixed Model Calibration (MIX-C)

Ready-to-use R code included!

Happy to share the first paper of my PhD is published☺️!

In case you like to use class imbalance corrections, maybe it is interesting. Let me know what you think!

onlinelibrary.wiley.com/doi/10.1002/...

Many thanks to @maartenvsmeden.bsky.social, @benvancalster.bsky.social, Anne, Kim and Carl !!

Time to say goodbye to the Julius center and the beautiful city of Utrecht 👋 In just 4 short months, I’ve gained invaluable experiences, connections, and good memories. Grateful for the opportunity to grow in such an inspiring place and special thanks to @maartenvsmeden.bsky.social for hosting me 💙

We have two vacancies for a postdoctoral and PhD researcher at Maastricht University. They will work on the development and application of value-of-information methods for the validation of clinical risk prediction models and medical AI.

links below

My favourite thing about the paper is this summary table

Just out as preprint our overview of 32 performance measures for clinical prediction models.

We recommend always including: AUROC, calibration plot, a clinical utility measure and a plot of probability distributions per outcome.

Fully reproducible code in Pyhton and R: github.com/benvancalste...

We've made the move across...so here’s a little thread introducing the various TRIPOD reporting guidelines to provide standards for #transparency and completeness of clinical prediction models to facilitate #reproducibility and guide #openscience

#MLSky #StatsSky #statistics #academia #EpiSky

Happy to share the first article of my PhD, which is now available as a pre-proof!

We looked at methods used to adjust existing (AI/ML) clinical prediction models to new contexts, like different hospitals, clinical domains or to a specific individual.

Curious to hear your thoughts!😃

IMO it’s a mistake to give stats to 1st year med students. It’s not why they chose medicine & they resent it. Better to wait until they have developed some curiosity for it. I argued unsuccessfully for this during my time at UCL.