Estimating the Effect of Early Treatment Initiation in Parkinson's Disease Using Observational Data onlinelibrary.wiley.com/doi/10.1002/md…

New #rstats technote: Moving away from Travis CI ropensci.org/technotes/2020…

"PhD Position on Causal Inference & Machine Learning" I was struck by this AD from TU Delft, The Netherlands, for putting CI first and ML second : tudelft.nl/over-tu-delft/… Evidently, the faculty at TU Delft understand where the future of ML lies. If qualified, I would apply.

Are you interested in pursuing a PhD in Machine Learning/Statistics? Join Prof. Elena Marchiori and me in developing models to better understand and predict cognitive decline! Application deadline: 18 November ru.nl/werken-bij/vac… #PhDposition #RStats #Python #DataScience

Dynamic prediction of mortality in COVID-19 patients in the intensive in the intensive care unit: A retrospective multi-center cohort study sciencedirect.com/science/articl…

Development and validation of an early warning model for hospitalized COVID-19 patients: a multi-center retrospective cohort study icm-experimental.springeropen.com/articles/10.11…

Causal inference using observational intensive care unit data: a systematic review and recommendations for future practice medrxiv.org/cgi/content/sh… #medRxiv

We are looking for a postdoc to come work with us on (machine learning) models for heterogeneous effect estimation at Radboud University. If you are interested in causal inference please consider applying: ru.nl/werken-bij/vac…

When can we detect unobserved confounders in observational data? While this question often is unanswerable, in my most recent paper (arxiv.org/abs/2205.13935) we are able to give an answer when we have data from multiple environments as in the scenario found in the figure. 1/n

#ArtificialIntelligence in #ICU, moving from predictive to actionable #AI: 🤖 ICM?? is about sequential decision-making 🤖 actionable AI to guide treatment choices: are we there yet? 🤖 future: ‘narrow AI’ rather than omnipotent ‘general AI’? #FOAMcc 🖇️ rdcu.be/dd4Yc

📣📣📣We are hiring ‼️‼️‼️ Check out the PhD position in trustworthy machine learning with knowledge utilization and reasoning at TU Delft! Apply by the end of August to come live in the beautiful Netherlands! RTs are appreciated🙌 tinyurl.com/reasoningPhD

Does k-means always improve with more data? Our paper proving the potential for strange (non-monotonic) learning curve behaviour for 2-means is now available: link.springer.com/article/10.100…

Our review of the use and reporting of causal inference using ICU data, led by Jim is out now! nature.com/articles/s4174…

Stepping out of the clinic! Just so incredibly proud of our #phd student Luc Evers who successfully defended his #thesis on how wearable sensors can help to bring both care and research back into the home of persons with #Parkinson. Great work, and outstanding public defence.

How can we safely use external data to improve statistical inference in randomized trials? Excited to finally share this new preprint with Guanbo Wang, Jesse Krijthe, and Issa Dahabreh that we started on during my stay in CAUSALab. Let's dive in! 🧵 arxiv.org/abs/2406.17971

Risk‐Based Decision Making: Estimands for Sequential Prediction Under Interventions onlinelibrary.wiley.com/doi/10.1002/bi…

Extremely happy that our 'Safe Causal Inference' consortium was granted! We will be hiring 8 PhD students to adress causal assumption violations, triangulation and causal model selection. With Jesse Krijthe Jeremy Labrecque - gone to Bluesky Aad vd Vaart & Stephanie vd Pas nwo.nl/en/news/64-mil…

Predicting benefit from adjuvant therapy with corticosteroids in community-acquired pneumonia: a data-driven analysis of randomised trials: sciencedirect.com/science/articl…

When can we falsify the assumption of no unmeasured confounding in observational studies? In our latest work, we develop a more efficient test for falsifying this assumption when we have data from multiple environments. A quick breakdown👇

We are hiring! Are you interested in causality, statistics and machine learning? We have an exciting PhD opportunity at TU Delft to improve trustworthiness of causal inference #PhDOpportunity #CausalInference #MachineLearning #Statistics careers.tudelft.nl/job/Delft-PhD-…