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Maarten van Smeden

@maartenvsmeden.bsky.social
11K followers 484 following 318 posts

statistician • associate prof • team lead health data science and head methods research program at julius center • director ai methods lab, umc utrecht, netherlands • views and opinions my own

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Maarten van Smeden @maartenvsmeden.bsky.social · 28/07/2026
To all academics
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Maarten van Smeden @maartenvsmeden.bsky.social · 20/07/2026
Don’t tell this to ChatGPT
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Aliëtte Jonkers @aliettejonkers.nl · 09/07/2026
Lang gewerkt aan de reconstructie van dit verhaal. Zaterdag in NRC, vandaag al online: Heeft de geit het weer gedaan? Het bewijs is broodmager dat omwonenden longontstekingen krijgen door de geitenhouderij Cadeaulink 🎁 www.nrc.nl/nieuws/2026/...
nrc.nl
Heeft de geit het weer gedaan? Het bewijs is broodmager dat omwonenden longontstekingen krijgen door de geitenhouderij
Volksgezondheid: Zijn geiten opnieuw een gezondheidsrisico, na de eerdere uitbraak van Q-koorts? Zorgen ze voor longontstekingen? Onderzoek dat dat zou aantonen, wordt „volledig mislukt” genoemd.
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Maarten van Smeden @maartenvsmeden.bsky.social · 06/07/2026
😂
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Maarten van Smeden @maartenvsmeden.bsky.social · 02/07/2026
Normality : a very rare shape for data www.linkedin.com/posts/maarte...
linkedin.com
Statistical terms: what they really mean Multicolinearity— these variables all look the same Heteroscedasticity— the variation varies Attenuation— being too modest Overfitting— too good to be… | Maar...
Statistical terms: what they really mean Multicolinearity— these variables all look the same Heteroscedasticity— the variation varies Attenuation— being too modest Overfitting— too good to be true Co...
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Maarten van Smeden @maartenvsmeden.bsky.social · 15/05/2026
Came across this gem again today. Still makes me giggle @richarddriley.bsky.social @gscollins.bsky.social Yes, it is published: pubmed.ncbi.nlm.nih.gov/32817260/
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Darren Dahly @statsepi.bsky.social · 28/04/2026
🎯So many important points packed into this editorial. ht @maartenvsmeden.bsky.social www.nature.com/articles/s41...
nature.com
Show us the evidence for the value of medical AI - Nature Medicine
Claims that medical AI is improving care must be backed by appropriate evidence.
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Eslam Maher @eslammaher.bsky.social · 25/03/2026
Appraising ML prediction models @maartenvsmeden.bsky.social 1) Share model and code 2) Predictors and language 3) Class imbalance & calibration 4) Model validation sample size 5) Is the model clinically useful in practice? www.jclinepi.com/article/S089...
jclinepi.com
Preliminary appraisal of machine learning based prediction models
A significant portion of healthcare research is devoted to the development of prediction models, yet the integration of these models into routine clinical care remains limited. Persistent barriers, su...
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Frank Harrell @f2harrell.bsky.social · 17/03/2026
Fantastic new paper casting doubt on explainability of explainable AI. To explain complex machine learning algorithms you need reproducibility of the explanation at a minimum academic.oup.com/ehjdh/articl... #machinelearning #Statistics #StatsSky @maartenvsmeden.bsky.social
academic.oup.com
Signal or noise? Evaluating commonly used attribution methods for explaining deep neural networks in electrocardiogram classification
AbstractAims. Attribution-based explainability methods are widely used in electrocardiogram (ECG) analysis to interpret predictions from ‘black-box’ deep n
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Ben Van Calster @benvancalster.bsky.social · 10/03/2026
Happy to see this in print! doi 10.1146/annurev-statistics-042324-123749 @maartenvsmeden.bsky.social @laurewynants.bsky.social @vanamsterdam.bsky.social and Ewout Steyerberg
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Maarten van Smeden @maartenvsmeden.bsky.social · 06/03/2026
I have got the data and I figured out exactly how to do my cluster analysis all I need is a relevant question that my cluster analysis is going to answer
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Donald Szlosek @dszlosek.bsky.social · 03/03/2026
What if you combine open datasets with AI? Apparently, a 3 fold increase in low quality research papers, mass-produced by paper mills. Interesting study in @jclinepi.bsky.social #academicsky #episky #medsky #Skystats Thanks to @maartenvsmeden.bsky.social for initially posting this on Linkedin!
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Ben Van Calster @benvancalster.bsky.social · 13/12/2025
Our guidance regarding performance measures for medical AI models is finally out! - Stop bashing AUROC, although it does not settle things - Calibration and clinical utility are key - Show risk distributions - Classification statistics (e.g. F1) are improper www.thelancet.com/journals/lan...
thelancet.com
Evaluation of performance measures in predictive artificial intelligence models to support medical decisions: overview and guidance
Numerous measures have been proposed to illustrate the performance of predictive artificial intelligence (AI) models. Selecting appropriate performance measures is essential for predictive AI models i...
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Maarten van Smeden @maartenvsmeden.bsky.social · 05/12/2025
NEW PAPER The use of explainable AI in healthcare evaluated using the well known Explain, Predict and Describe taxonomy by Galit Shmueli link.springer.com/article/10.1...
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Maarten van Smeden @maartenvsmeden.bsky.social · 27/11/2025
🧐
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Cameron Patrick @cameronpat.bsky.social · 25/11/2025
this is one of my favourite observations about sample size calculations. (afaik first articulated by Miettinen in 1985)
"On the first, and pivotal, level the decision is a binary one—the
choice between zero and nonzero as the size. Validity considerations alone are often sufficient to imply that zero is the optimal size"

- O. S. Miettinen "Theoretical Epidemiology" (1985)
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Maarten van Smeden @maartenvsmeden.bsky.social · 25/11/2025
For some research studies the optimal sample size should be estimated at 0
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Maarten van Smeden @maartenvsmeden.bsky.social · 18/11/2025
“Data available upon reasonable request” is academic language for you can get my data OVER MY DEAD BODY
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Maarten van Smeden @maartenvsmeden.bsky.social · 14/11/2025
Manuscript_Final_Version_actualFINALcopy_version9b_USETHISONE.docx
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Maarten van Smeden @maartenvsmeden.bsky.social · 08/10/2025
Kind reminder: data driven variable selection (e.g. forward/stepwise/univariable screening) makes things *worse* for most analytical goals
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Maarten van Smeden @maartenvsmeden.bsky.social · 25/09/2025
NEW FULLY FUNDED PHD POSITION Looking for a motivated PhD candidate to join our team. Together with Danya Muilwijk, Jeffrey Beekman and I, you will explore opportunities and limitations of AI in the context of organoids For more info and for applying 👉 www.careersatumcutrecht.com/vacancies/sc...
careersatumcutrecht.com
Vacancy — PhD position on AI methodology for prediction of patient outcomes using organoid models
Are you passionate about bringing personalized medicine to the next level and make real impact in healthcare? Join our team and develop novel AI methodology to improve predictions of relevant patient ...
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Darren Dahly @statsepi.bsky.social · 22/09/2024
Interpretable "AI" is just a distraction from safe and useful "AI"
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Maarten van Smeden @maartenvsmeden.bsky.social · 19/08/2025
No.
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Maarten van Smeden @maartenvsmeden.bsky.social · 13/08/2025
I wonder who those people are who come here dying to know what GenAI has done with some prompt you put in
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Maarten van Smeden @maartenvsmeden.bsky.social · 12/08/2025
If you think AI is cool, wait until you learn about regression analysis
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Maarten van Smeden @maartenvsmeden.bsky.social · 11/08/2025
NEW PREPRINT Explainable AI refers to an extremely popular group of approaches that aim to open "black box" AI models. But what can we see when we open the black AI box? We use Galit Shmueli's framework (to describe, predict or explain) to evaluate arxiv.org/abs/2508.05753
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Maarten van Smeden @maartenvsmeden.bsky.social · 31/07/2025
The healthcare literature is filled with "risk factors". This word combination makes research findings sound important by implying causality, while avoiding direct claims of having identified causal associations that are easily critiqued.
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Maarten van Smeden @maartenvsmeden.bsky.social · 23/07/2025
When forced to make a choice, my choice will be logistic regression model over linear probability model 103% of the time
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Tim Morris @timpmorris.bsky.social · 23/07/2025
Post just up: Is multiple imputation making up information? tldr: no. Includes a cheeky simulation study to demonstrate the point. open.substack.com/pub/tpmorris...
Cover picture with blog title & subtitle, and results graph in the background
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Darren Dahly @statsepi.bsky.social · 14/07/2025
You can have all the omni-omics data in the world and the bestest algorithms, but eventually a predicted probability is produced & it should be evaluated using well-established methods, and correctly implemented in the context of medical decision making. statsepi.substack.com/i/140315566/...
The leaky pipe of clinical prediction models. by @maartenvsmeden.bsky.social‬ et al
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Maarten van Smeden @maartenvsmeden.bsky.social · 10/07/2025
Depending which methods guru you ask every analytical task is “essentially” a missing data problem, a causal inference problem, a Bayesian problem, a regression problem or a machine learning problem
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Darren Dahly @statsepi.bsky.social · 07/07/2025
Copy of the title page of John Snow's seminal "Mode of communication of Cholera" report, with the text "A real world evidence study" in comic sans added to it.
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Richard Riley (R²) @richarddriley.bsky.social · 27/06/2025
* New preprint led by Joao Matos & @gscollins.bsky.social "Critical Appraisal of Fairness Metrics in Clinical Predictive AI" - Important, rapidly growing area - But confusion exists - 62 fairness metrics identified so far - Better standards & metrics needed for healthcare arxiv.org/abs/2506.17035
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Maarten van Smeden @maartenvsmeden.bsky.social · 27/06/2025
Surprisingly common thing: comparisons of prediction models developed using, say, Logistic Regression, Random Forest and XGBoost with conclusion XGBoost is "good" because it yields slightly higher AUC than LR or RF using the same data Fact that "better" doesn't always mean "good" seems lost
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Georg Heinze @georgheinze.bsky.social · 26/06/2025
Published: the paper 'On the uses and abuses of Regression Models: a Call for Reform of Statistical Practice and Teaching' by John Carlin and Margarita Moreno-Betancur in the latest issue of Statistics in Medicine onlinelibrary.wiley.com/doi/10.1002/... (1/8)
onlinelibrary.wiley.com
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Maarten van Smeden @maartenvsmeden.bsky.social · 17/06/2025
What is common knowledge in your field, but shocks outsiders? Validated does not mean it works as intended. It means someone has evaluated it (and may have concluded it doesn’t work at all)
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Richard Riley (R²) @richarddriley.bsky.social · 02/06/2025
**New Lancet DH paper** "Importance of sample size on the quality & utility of AI-based prediction models for healthcare" - for broad audience - explains why inadequate SS harms #AI model training, evaluation & performance - pushback to claims SS irrelevant to AI research 👇 tinyurl.com/yrje52fn
sciencedirect.com
Importance of sample size on the quality and utility of AI-based prediction models for healthcare
Rigorous study design and analytical standards are required to generate reliable findings in healthcare from artificial intelligence (AI) research. On…
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Eric Smith @ericsmithrocks.bsky.social · 31/05/2025
People always ask me, “how do I know my manuscript is done?” There’s only one way, my friends. If your file name looks something like this: Manuscript - Final Draft 3.7 FINAL FINAL - FINAL (5).docx Then, and only then, is it time.
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Maarten van Smeden @maartenvsmeden.bsky.social · 27/05/2025
Re-proposing the Occam's taser: an automatic electric shock for anyone riding the AI hype train making their models unnecessarily complex
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Maarten van Smeden @maartenvsmeden.bsky.social · 27/05/2025
Rule of thumb: If your model requires data to look like this (balanced after SMOTE), then maybe you want to use a different model
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Maarten van Smeden @maartenvsmeden.bsky.social · 19/05/2025
We should really ban all use of AI from all our education because the use of AI will make our students dumb, and banning innovation has worked really well before
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Maarten van Smeden @maartenvsmeden.bsky.social · 19/05/2025
As scientists it is difficult to stay in love with the questions once you fall in love with the answers
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Tim Morris @timpmorris.bsky.social · 14/05/2025
So glad they let us use this turn-of-phrase @maartenvsmeden.bsky.social doi.org/10.1016/j.jc...
Screenshot says ‘To a systematic-reviewer, the results of groups A to D may feel like turning up with a dustpan and brush after an earthquake because:’
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Maarten van Smeden @maartenvsmeden.bsky.social · 12/05/2025
So.... about using large language models (e.g. chatGPT) for writing motivation letters for a job I get it! And honestly, use all the technology you need to write the best letter you can But after reading dozens of letters with almost EXACTLY the same intro paragraph I do get a bit tired of it
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Nicole Erler @nerler.bsky.social · 11/05/2025
Only 5 days left to apply for our 3 PhD positions at the @umcutrecht.bsky.social 🎓 🏃🏃‍♀️
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Maarten van Smeden @maartenvsmeden.bsky.social · 09/05/2025
Code or it did not happen
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Tim Morris @timpmorris.bsky.social · 06/05/2025
‘Wow, this treatment was no better than placebo – because the placebo was so effective!’ It’s such a shame the term ‘placebo effect’ is so widely known and used. There are fundamental challenges with identifying it and most of the claims don’t even try. It’s just change-from-baseline every time.
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Maarten van Smeden @maartenvsmeden.bsky.social · 01/05/2025
Before citing a paper the least you can do is thoroughly read… 1st year student: the entire literature on the subject Grad student: the paper you cite Post-grad: title and abstract and scan the rest of the paper Professor: the title. PLEASE read the title
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Gary Collins @gscollins.bsky.social · 30/04/2025
recommendations on which prediction model performance measures to report and which not too by @benvancalster.bsky.social more discussion here… arxiv.org/abs/2412.10288 #memtab
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Gary Collins @gscollins.bsky.social · 30/04/2025
next up is @joieensor.bsky.social talking about his work on software implementation for sample size calculations for targeting precise risk predictions - code available to do this available here github.com/JoieEnsor/pm... #memtab
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