Pre-print alert: Many ECG-AI models have been developed to predict a wide range of cardiovascular outcomes. But, underrepresentation of women in cardiovascular studies raises the question: Are ECG-AI models equally predictive for women and men with sex-imbalanced training data?

New paper in @annalsofim.bsky.social "50 ways to misinterpret clinical prediction models for treatment decisions” --> Published version: www.acpjournals.org/doi/10.7326/... --> Open access version: arxiv.org/pdf/2402.17366

The Risks of Risk Assessment: Causal Blind Spots When Using Prediction Models for Treatment Decisions | Annals of Internal Medicine

Clinicians increasingly rely on prediction models to guide treatment choices. Most prediction models, however, are developed using observational data that include some patients who have already receiv...

acpjournals.org

BMS-ANed Spring Meeting on Thursday, June 19 Time: 13:00–18:00 (CEST) Location: Vredenburg 19, 3511 BB, Utrecht Details and registration: vvsor.nl/biometrics/e...

Hans van Houwelingen award ceremony and symposium June 19th 2025 - VVSOR

This spring, the BMS-ANed organises an in-person meeting:

vvsor.nl

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!

Oisín Ryan@oisinryan.bsky.social · 2y ago

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

Which is stronger evidence for robustness? When evaluating predictive performance of one model in several different environments (e.g. regions / hospitals): A. stable discrimination (AUC) and calibration in all environments B. stable discrimination, varying calibration vote with 👍=A; ❤️=B

ask chatGPT o3 this before submitting your next paper to, I got ~10 usable comments out of it: you're a reviewer for <journal>; review the attached paper when you're either:

Very excited for my first (belated) visit to #EuroCIM2025! I'm here with 3 bits of work: 1. a poster on a causal understanding of prediction model performance under shifts in 'case-mix' (or covariate / outcome drift); I show how discrimination and calibration respond differently bit.ly/ccm-arxiv

this seems pretty cool: an overview of llms for statisticians arxiv.org/abs/2502.17814

An Overview of Large Language Models for Statisticians

Large Language Models (LLMs) have emerged as transformative tools in artificial intelligence (AI), exhibiting remarkable capabilities across diverse tasks such as text generation, reasoning, and decis...

arxiv.org

Vacancy for a postdoc position. Improve the transparency of decision support algorithms by figuring out how we can quantify and communicate uncertainty in individual causal predictions. With Marleen Kunneman, Daniala Weir and me. Three more days to apply 👇 www.lumc.nl/en/about-lum...

Postdoc Biomedical Data Scientist / Biostatistician | LUMC

In this postdoc position at LUMC, you will work on groundbreaking research that enhances the transparency and trustworthiness of decision support algorithms in healthcare. This position allows you to ...

lumc.nl

Digital twins are useful insofar as they reflect causal mechanisms Don't think a generative model ('digital twin') can inform treatment decisions just because it procudes different outputs when you give it different inputs. Doesn't matter if it's 'AI' or not.

saliency maps are the new table 2 fallacy

Liking this interaction with @mmbronstein.bsky.social and Denis Danilov so much I'm reposting it here

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

Can someone make a "science-not-politics" starter pack? Great respect for academics who are politically engaged, and yes, bsky/X are places for political discussion / news sharing. But science and politics take different parts of my brain; can we get science without political distractions?

Look at @maartenvsmeden.bsky.social go, he's won the VIDI grant! (arguably the most prestigious personal grant in the Netherlands at his career stage). Congrats!

Maarten van Smeden@maartenvsmeden.bsky.social · 2y ago

Feeling grateful today for receiving a VIDI personal grant This grant will allow us to develop better methods to ensure AI-based decision support systems in healthcare will remain safe and effective to use over time www.nwo.nl/en/news/102-...

Anyone else here afraid we’re enjoying a VC backed honeymoon on this platform, and that once we’ve (re-)established a valuable network, the money-making ad-serving attention-grabbing algorithms will kick in and spoil the fun?

Rose 🌹@rose.bsky.team · 2y ago

People keep asking how we make money. Fair q. Right now, we are supported by funds and angel investors bc our focus is on the user experience & dev ecosystem. More immediate $ plans coming soon. Most importantly, we won’t hyperfinancialize the social experience. (& we don’t sell your data!)

We're still accepting applications for this PhD position, send in your application by Oct 29!

Wouter van Amsterdam@vanamsterdam.bsky.social · 2y ago

new PhD position with @maartenvsmeden.bsky.social and me! are you: - interested in the intersection of "science" and deep learning? - keen to work with electrocardiography (ECG) data - eager to learn and be part of a vibrant data science team of the UMC Utrecht? see bit.ly/3UaSN23

hahaha, "Granger Danger"

Will Lowe@conjugateprior.org · 2y ago

Unwisely concluding that X causes Y because Y tends to follow X needs a better name than this. I suggest: Granger Danger

Created a new group replacing and updating a list I enjoyed following on the bird site. Mostly people posting on medical stats and DS/AI ICYI: go.bsky.app/ArqEz36

Medical stats/ds/ai

Join the conversation

go.bsky.app

new PhD position with @maartenvsmeden.bsky.social and me! are you: - interested in the intersection of "science" and deep learning? - keen to work with electrocardiography (ECG) data - eager to learn and be part of a vibrant data science team of the UMC Utrecht? see bit.ly/3UaSN23

Vacancy — PhD student SciML4Medicine

PhD student SciML4Medicine: electrocardiography analysis with mathematical modeling and deep learning.

bit.ly

Joost van Rosmalen from #umcutrecht kicking of the Causal Inference for AI meetup with his talk on using data from historical controls for trials with dynamic borrowing methods

We're hosting a Causal AI meet-up with Nan van Geloven, Jesse Krijthe, @oisinryan.bsky.social and @jeremylabrecque.bsky.social - this time focussed on Health, Speakers: Joost van Rosmalen, Dimitri Rizopoulos and Doranne Thomassen University Library Utrecht USP (Boothzaal) Sep 23, 14.30-17.00

Want to learn how observational data can give insight into causal effects? How to specify a target trial & use prediction models for causal insight? Sign-up now for "Intro to Causal Inference and Causal Data Science", Aug 5-9 Utrecht: utrechtsummerschool.nl/courses/heal... @vanamsterdam.bsky.social

Ever need to do many repeated analyses? e.g. power calculations, sensitivity analyses, then speed becomes a crucial! In this blog post I compare newcomers #Julia google's #JAX versus #R for logistic regression TLDR: Julia wins, ~10x faster than R vanamsterdam.github.io/posts/240308...