I mostly agree but maybe this interests you: https://www.nature.com/articles/s41591-024-02902-1

Causal machine learning for predicting treatment outcomes - Nature Medicine

Causal machine learning methods could be used to predict treatment outcomes for subgroups and even individual patients; this Perspective outlines the potential benefits and limitations of the approach...

🤓 Du bist Student in München und würdest gerne mehr über transparente Forschungsmethoden erfahren und an spannenden Diskussionen über die Wissenschaft teilnehmen? Dann besuche den ReproducibiliTea Journal Club bei einer seiner nächsten Sitzungen! www.osc.uni-muenchen.de/members/repr...

Interesting! Will remote participation be possible for this session/conference? This would be incredibly helpful for planning my travel and deciding which conferences to attend.

Miniconference on novel applications of AI and ML in drug discovery and development (remote possible) #episky#causalskyhttps://asa-ct.github.io/miniconf2024/

This has been a requirement for BMJ submissions for years

The story about the xz backdoor is an interesting read https://boehs.org/node/everything-i-know-about-the-xz-backdoor

Everything I know about the XZ backdoor

Please note: This is being updated in real time. The intent is to make sense of lots of simultaneous discoveries

A whole bunch of tidymodels releases just made it to #rstatswww.tidyverse.org/blog/2024/03...

Fair machine learning with tidymodels - Tidyverse

Recent tidymodels releases integrated a set of tools for assessing whether machine learning models treat groups of people differently.

G-estimation is often called an S-learner in the causal machine learning literature causaldm.github.io/Causal-Decis...