Plug-and-play use of tree-based methods: Consequences for clinical prediction modelling - Journal of Clinical Epidemiology www.jclinepi.com/article/S089...

Written together with @ewoudschuit.bsky.social, Carl Moons & Tuur Leeuwenberg 🙏

New paper! 😃 We talk about using tree-based methods, such as Random Forests, for clinical prediction & what (not) to expect from them, with many illustrations. Let me know what you think!
doi.org/10.1016/j.jc...

Still some spots available in our summer school on all things causal inference, 7-11 July in Utrecht! Discounts for those working in universities and non-profits, and affordable accommodation offered by @utrechtuniversity.bsky.social summer school!

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 !!

This might be the first time after 10 years that boosted trees are not the best default choice when working with data in tables.
Instead a pre-trained neural network is, the new TabPFN, as we just published in Nature 🎉

Ah, too bad! It would be interesting to know more about how you designed those data and how you made those choices.. but anyway, eager to try it so already very nice that’s possible!

Very interesting work! I am especially intrigued by the synthetic datasets. I saw the code is not available , but is there more detailed information about this than in the article ? Like, how often you used certain connection types, how you generated missing data, etc. Would love to know more!

Some time ago I wrote a non-technical introduction to marginal effects, in case you don't know the underlying logic yet. The idea is to use your model as a prediction machine that can be queried to return answers to precisely the questions you're interested in.

www.the100.ci/2022/05/27/%...

Oops, forgot the link www.jclinepi.com/article/S089...

With many thanks to everyone who contributed, including @ewoudschuit.bsky.social @maartenvsmeden.bsky.social @mattsperrin.bsky.social @nielspeek.bsky.social @glenmartin.bsky.social and more who are not on Bluesky 🦋

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!😃

Interested in how to use non-experimental data to answer causal research questions? Mystified by DAGs and counterfactuals? Want to learn what Target Trial Emulation is all about?

Sign up now for the 2nd edition of our summer school, 7-11 July in Utrecht, with @vanamsterdam.bsky.social & BPdeVries