Asst Prof of Biostat @WashUMedi2db @WashUMedicine. Causality for reliable and responsible AI in health. Past: @ColumbiaDBMI, @Harvard, @BU_Tweets. Views mine.
βDo retinal images add prognostic value beyond EHRs in real-world clinical care? β We developed a multimodal AI framework that integrates retinal OCT imaging + EHR data to predict visual improvement in patients with diabetic macular edema (DME) receiving anti-VEGF therapy.
Using real-world data from
π₯ 973 patients
π₯ 14 hospitals across WashU/BJC Health System
ποΈ 196k OCT images
π 22,227 EHR features
We found
β OCT provides complementary prognostic information beyond structured EHR data
β Multimodal EHR+OCT models improved visual improvement prediction and risk stratification
β Foundation model choice matters β RETFound showed the strongest prognostic value
β Different ophthalmic foundation models capture very different types of clinical information
This work highlights both the promise and the challenges of deploying multimodal foundation models in real-world clinical settings.
π Preprint: https://t.co/d974uzKHsT
Huge thanks to my amazing student Siqi Sun and our amazing collaborators Cindy Cai, Cecilia S. Lee, Aaron Y. Lee, and Marc Suchard! Suggestions are welcome and appreciated!
@WashUMedi2db@washumeddovs@washumedgmg@washudeptmed
#Ophthalmology #MultimodalAI #FoundationModels #RealWorldEvidence #MachineLearning #MedicalAI #OCT #EHR #DiabeticMacularEdema #Retina
Very proud mentor moment today at #ENAR2026.
Yesterday, my PhD co-advisee Yiqiao Jin presented his work on Federated R-Learner for Estimating Conditional Average Treatment Effects across Heterogeneous Datasets. His work receives the #ENAR Distinguished Student Paper Award. This is a highly competitive award, with 186 submissions and only 21 papers selected this year.
As a junior faculty member, moments like this are deeply meaningful. One of the most rewarding parts of academia is watching students grow into confident researchers and seeing their work recognized by the community.
Iβm very grateful to Nan Lin, Yiqiaoβs co-mentor in the Department of Statistics & Data Science, for the fantastic collaboration and mentorship. I also want to thank both the Department of Statistics & Data Science and the WashU Institute for Informatics, Data Science and Biostatistics (I2DB) for creating such a collaborative research environment where interdisciplinary ideas like this can grow.
#ENAR2026 @WashUMedi2db
Yiqiao Jin, a PhD student in Statistics and Data Science, has been selected to receive one of the International Biometric Society Eastern North American Regionβs (ENAR) Distinguished Student Paper Awards for his paper.
π Read more: https://t.co/V8uG2lWXV4
@Z_Linying led WashU's team in a nationwide OHDSI study on semaglutide & diabetic retinopathy, published in @DiabetesRC. Data from 800K+ users found no increased risk of vision-threatening diabetic eye complications.
π Read more β https://t.co/wry49FNr47
π Exciting keynote at the BIDS retreat! Dr. Cecilia Lee shared her groundbreaking work in #OphthalmologyAI at @WashUMedi2db showcasing how AI + big data can transform eye care and beyond. ποΈπ€
Congrats to Dr. Siqi Sun & Dr. Linying Zhang on presenting at CVPR 2025 Workshop on MMFM-BIOMED! π Their model estimates causal effects from EHRs & chest X-rays.π #AI#Biomedicine#CVPR2025 @CausAI_Lab
Excited to kick off the spring semester seminar series with Dr. Yevgeniy Vorobeychik! @WashUengineers Dive into the intersection of privacy, utility, and fairness in biomedical research today at @BeckerLibrary, room 502. Donβt miss it!
#WashUMed
Join our Speaker Series with Yevgeniy Vorobeychik, PhD, MSE, Computer Science & Engineering, @WashUengineers! Topic: "Privacy, Utility, and Fairness in Biomedical Research" at @BeckerLibrary, room 502.
πhttps://t.co/30o2VXSnAI
#WashUMed
Upgrade your #causalinference arsenal.
A revision of our book "Causal Inference: What If" is available at https://t.co/3rrh0l8nFu
Thanks to everyone who suggested improvements, reported typos, and proposed new citations and material.
Enjoy the #WhatIfBook. Also, it's free.
We are excited to announce that @Z_Linying will receive the AMIA Edward H. Shortliffe Doctoral Dissertation Honorable Mention at #AMIA2024 for her dissertation!
π Nov. 11
π 1:45-3:15 p.m.
π Franciscan B
π https://t.co/D3eenHAA1O
#WashUMed#AMIA@AMIAinformatics
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 papers!
Iβm very honored to receive this award! Thanks to my mentors Drs George Hripcsak and David Blei, and committee members @noemieelhadad@proftatonetti@yixinwang_ for their guidance and support. Thanks to @ColumbiaDBMI faculties, students, and staffs and @OHDSI collaborators for making this journey fun and meaningful!
π AMIA is thrilled to announce the 2024 Edward H. Shortliffe Doctoral Dissertation Award winners!
First Prize: Alice Tang, MD, University of California, San Francisco
Honorable Mention: Linying Zhang, PhD, Columbia University
Read the press release: https://t.co/nHN6yV6eWr