Want to build fair AI models using EHRs but don’t know how? Come to poster 34 at #SAIL24 to learn about using #causality and #AI to explain observed disparities in clinical practice! Symposium on AI for Learning Health Systems @WashUi2db Columbia DBMI

Happy to welcome George Hripcsak, Prof. of Biomedical Informatics at Columbia University, to lead our next U.S. FDA CBER BEST Seminar on May 22 (11 am ET). Topic: Reliability in Observational Research: Assessing Covariate Imbalance in Small Studies Link/abstract: ohdsi.org/cber-best-semi…

Tomorrow I will present preliminary findings from our real-world effectiveness study of medications for opioid use disorder. #rwe #oud #moud

📢 Excited to announce the "AI for Reliable and Equitable Real-World Evidence Generation in Medicine" workshop at #AIME2024 on July 9, 2024, in Salt Lake City! 🌟 Join experts from informatics, biostatistics, computer science, and more as we explore AI's transformative role in

Very successful #AIME2024 Workshop on AI for Reliable and Equitable Real-World Evidence Generation in Medicine. Thanks to Dr. Zhang Linying Zhang for the invite. Nice meeting all the panelists, rising stars and the keynote speaker Dr. Hripcsak. Nice view from UU University of Utah Health Biomedical Informatics

My dissertation won the AMIA 2024 Edward H. Shortliffe Doctoral Dissertation Award Honorable Mention! Look forward to giving a talk on my dissertation "Causal machine earning for reliable real-world evidence generation in healthcare" at #AMIA2024 Annual Symposium. Dissertation is

Very important work! Congrats Gamze Gürsoy

Welcome Linying Zhang, PhD, who joins #WUDeptMedicine Division of General Medicine & Geriatrics. ⁠ ⁠ Dr. Zhang’s research focuses on improving reliability of real-world evidence generation using causal inference and artificial intelligence. ⁠ Link> l8r.it/xEZ5

I’m very honored to receive this award! Thanks to my mentors Drs George Hripcsak and David Blei, and committee members Noémie Elhadad Nicholas Tatonetti Yixin Wang for their guidance and support. Thanks to Columbia DBMI faculties, students, and staffs and OHDSI collaborators for

10 years ago, ML papers were math-heavy. Advice I got: less math, more empirics. Today, many ML/AI papers lack even a single math formula, let alone math thinking. My advice to young LLM researchers: do a little math if possible. It'll distinguish yours from the sea of LLM

It was a tremendous honor for me to receive the OHDSI Titan Award! Thanks OHDSI for this recognition! #OHDSI2024

Thank you, OHDSI community, for an amazing #OHDSI2024! #JoinTheJourney

I’m excited too! Come see me present my 100+ pages of dissertation in under 40 mins ;) Will I make it? 🤓

A great causal inference book by Miguel Hernán and James Robins. Excited for its upgrade.

Excited to kick off the spring semester seminar series with Dr. Yevgeniy Vorobeychik! WashU McKelvey Engineering Dive into the intersection of privacy, utility, and fairness in biomedical research today at WashU Medicine Becker Library, room 502. Don’t miss it! #WashUMed

Congrats to Siqi!

Excited to have my undergrad summer intern Xiaoyu Klay Sun, from our BIDS@I2DB program, working on applying AI for fluid segmentation in macular OCT images — and he presented this work at our retreat! Love seeing the next generation tackle real-world challenges in ophthalmology.

🚀 Exciting keynote at the BIDS retreat! Dr. Cecilia Lee shared her groundbreaking work in #OphthalmologyAI at WashU Informatics, Data Science and Biostatistics showcasing how AI + big data can transform eye care and beyond. 👁️🤖

Proud to contribute to this OHDSI network study! Kudos to the study lead Cindy X. Cai Johns Hopkins Medicine and the team!