Lotta Meijerink
@lottameijerink.bsky.social
PhD student @ Julius Center, UMC Utrecht | causal inference 🤝clinical prediction
Written together with @ewoudschuit.bsky.social, Carl Moons & Tuur Leeuwenberg 🙏
June 5, 2025 at 3:07 PM
Written together with @ewoudschuit.bsky.social, Carl Moons & Tuur Leeuwenberg 🙏
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!
January 9, 2025 at 12:02 PM
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!
January 9, 2025 at 11:08 AM
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!
Reposted by Lotta Meijerink
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/%...
www.the100.ci/2022/05/27/%...
✨ Unleash your inner stats sparkle ✨ with this very non-technical introduction to marginal effects
Let’s admit right away that “marginal effects” doesn’t sound like the most sexy topic. I’m not saying that to further marginalize these poor effects. It’s just that statistics, in and of itself, barel...
www.the100.ci
December 13, 2024 at 12:05 PM
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/%...
www.the100.ci/2022/05/27/%...
Oops, forgot the link www.jclinepi.com/article/S089...
Updating methods for AI-based clinical prediction models: a scoping review
To give an overview of methods for updating AI-based clinical prediction models based on new data.
www.jclinepi.com
December 13, 2024 at 1:16 PM
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 🦋
December 13, 2024 at 1:07 PM
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 🦋