So fun to listen to three outstanding leaders and researchers in informatics to talk about their career!

Call for Submissions to the AI for Reliable and Equitable Real-World Evidence Generation in Medicine Workshop #AI #RWE at the 22nd International Conference on AI in Medicine ( #AI ME). Check out the workshop here: medicine.utah.edu/dbmi/aime/ai-r… WashU Informatics, Data Science and Biostatistics Yves Lussier

👏BIG THANKS👏 to Philip Payne, PhD (Philip R.O. Payne, PhD) Director of I2DB, Becker Professor & Director @WashUi2 & Chief Data Scientist Washington U. Med for presenting his DBMI Special Seminar on #AI & Learning Health Systems!

ICYMI: Watch the recording below!👇
youtu.be/pZod2kOFPcQ

And the resulting data - thousands of cancer pathology reports - is freely available. See here github.com/tatonetti-lab/…

We are thrilled to welcome Dr. Yong Chen (Yong Chen), Professor of Biostatistics at Penn Medicine, to lead our U.S. FDA CBER BEST Seminar this Wednesday, April 17 (11 am ET). This virtual session is open to everybody. Key links are on our homepage: ohdsi.org/cber-best-semi…

I study causal informatics. Period. Thanks Miguel Hernán for making my future self-introduction so much easier, and for a great keynote talk with successes and failures towards reliable RWE! #IS24 #AMIA

A great tool for designing comparative observational studies! For causal inference enthusiasts, this tool helps design a study that is less prone to violation of overlap!

Join us at the 2024 I2DB Symposium on AI in Medicine, April 12. The symposium features abstract submission and a datathon of AI for clinical predictive modeling. Submit your abstract and register for the datathon today! The deadline is Mar 8. i2db.wustl.edu/calendar_event…

🎊Our abstract on “Building causally explainable fair learning health system” (w/ Xinzhuo Jiang, Karthik Natarajan, and George Hripcsak) was accepted at #SAIL24 !! Thanks Symposium on AI for Learning Health Systems for the travel award! See you in May at Puerto Rico 🏖️🍸! @washui2db Columbia DBMI

Look forward to Miguel Hernán speaking at #AMIA2024 Informatics Summit!

Look forward to giving a talk on causal machines learning for RWE and my research journey with the OHDSI community. Tomorrow at noon Central Time. Msg me for a zoom link.

🎉 HAPPY BIRTHDAY OHDSI! 🎉

10 years ago, the OHDSI community officially formed. We grow each day globally, and our impact has already been felt. Thank you to everybody who has joined the journey. We believe even greater things are coming over the next 10 years! #JoinTheJourney

Exciting news! Our new Nature Communications
paper is online: Scaling Target Trial Emulation by simulating hundreds of randomized controlled trials using two types of Real-World Data EHR and MarkestScan claims to identify drug repurposing candidates for #AD using #RWE

Super informative and visionary panel on #GenerativeAI and #LLM for health ML4H. My takeaway is that AI + knowledge > AI in terms of ability of causal reasoning, generalizability, and transportability.

If you are struggling about real-world evidence #reliability , model #generalizability , algorithmic #fairness , and knowledge-guided ML, join me at @ML4H this Sunday at the #Causality roundtable! We will explore the many ways that causality can help address all these questions.

🌟 Exciting PhD Opportunity in #BiomedicalInformatics at WashU Informatics, Data Science and Biostatistics @washudbbs🌟

📅 Deadline: Dec 1st

Join me to improve healthcare with causal modeling and machine learning/AI! Apply to the Biomedical Informatics and Data Science (BIDS) PhD program 👉dbbs.wustl.edu/programs/biome…