"Developing a National-Scale Rare Disease Screening Program Using Foundation Models"
Alison Callahan, PhD.
Thursday, April 16th, 2026
12:00 to 1:00 pm PST
Live Stream: stanford.zoom.us/j/9788759601...
Webinar ID: 978 8759 6012
Webinar Passcode: 420642
“What a Language Model Remembers, What It Finds, and What It Has to Be Told”
Ian M. Campbell, MD, PhD.
Thursday, April 9th, 2026
12:00 to 1:00 pm PST
Live Stream: stanford.zoom.us/j/9788759601...
Webinar ID: 978 8759 6012
Webinar Passcode: 420642
“Best Practices for Secondary Clinical Data Use Sharing or Accessibility”
Jason Fries, PhD, Tina Hernandez-Boussard, PhD, Curt Langlotz, MD, PhD
Thursday, April 2nd, 2026
12:00 to 1:00 pm PST
Live Stream: stanford.zoom.us/j/9788759601...
Webinar ID: 978 8759 6012
Webinar Passcode: 420642
New on the #FutureofMedicine: #StanDOM clinician & AI researcher @jonc101.bsky.social joins host @euanashley.bsky.social to explore what happens when AI meets real-world medicine—& why the results aren't always what we expect.
▶ Watch: https://bit.ly/4sKbtoC
🎧 Listen: https://bit.ly/43LGRZv
“Holistic Evaluation of Large Language Models for Medical Tasks with MedHELM”
Suhana Bedi
Thursday, March 12th, 2026
12:00 to 1:00 pm PST
Live Stream: stanford.zoom.us/j/9788759601...
Webinar ID: 978 8759 6012
Webinar Passcode: 420642
“Towards the AI Doctor: Utah and Beyond”
Byron Crowe, MD, MSc.
Thursday, March 5th, 2026
12:00 to 1:00 pm PST
Live Stream: stanford.zoom.us/j/9788759601...
Webinar ID: 978 8759 6012
Webinar Passcode: 420642
“Do Contemporary Advances in AI Require Change in the Fundamental 'Theorem' of Informatics?”
Charles P. Friedman, PhD.
Thursday, February 26th, 2026
12:00 to 1:00 pm PST
Live Stream: stanford.zoom.us/j/9788759601...
Webinar ID: 978 8759 6012
Webinar Passcode: 420642
“Advice for Those (Maybe) Interested in Starting a Company”
Alexander Morgan, MD, PhD.
Thursday, February 19th, 2026
12:00 to 1:00 pm PST
Live Stream: stanford.zoom.us/j/9788759601...
Webinar ID: 978 8759 6012
Webinar Passcode: 420642
“Predict, Prevent, Personalize - Health AI at Northwell Health”
Theodoros Zanos, PhD.
Thursday, February 12th, 2026
12:00 to 1:00 pm PST
Live Stream: stanford.zoom.us/j/9788759601...
Webinar ID: 978 8759 6012
Webinar Passcode: 420642
The magic of AI in health care: Beyond the illusion | 90 Seconds w/ Lisa Kim
www.youtube.com/watch?v=cdXz...
“A Unified Molecular Framework for Quantifying Immune Dysregulation Across Health, Diseases, and Treatment Response”
Purvesh Khatri, PhD.
Thursday, January 29th, 2026
12:00 to 1:00 pm PST
Live Stream: stanford.zoom.us/j/9788759601...
Webinar ID: 978 8759 6012
Webinar Passcode: 420642
“Precision Medicine for Hospital Care: From Bedside Insight to Clinical Impact”
Tim Sweeney MD, PhD.
Thursday, January 22nd, 2026
12:00 to 1:00 pm PST
Live Stream: stanford.zoom.us/j/9788759601...
Webinar ID: 978 8759 6012
Webinar Passcode: 420642
Liam McCoy is a resident physician in neurology at the University of Alberta, and Research Affiliate at the Massachusetts Institute of Technology. He engages in research related to the effective, ethical integration of clinical reasoning AI systems in practical healthcare.
Dr. Peter Brodeur is a rising cardiology fellow at Harvard Medical School’s Beth Israel Deaconess Medical Center. Dr. Brodeur is an affiliate of ARISE, reviewer for NEJM AI, and former life sciences strategy consultant. human computer interaction and LLM clinical reasoning.
Thursday, January 15th, 2026
12:00 to 1:00 pm Pacific Time
Zoom Link:
Live Stream
stanford.zoom.us/j/9788759601...
Webinar ID:
978 8759 6012
Webinar Passcode: 420642
"... often don’t translate to safer or better care.
The goal is to give a clear, evidence-based picture of where clinical AI actually stands today, what the public should trust (and not), and what will determine whether these tools genuinely improve care in the years ahead."
"...a review of the most impactful studies published in 2025.
We separate real progress from overstatement: where AI meaningfully improves prediction, diagnosis, and clinical workflows, and where it still fails. We also examine why impressive benchmark results..."
Colloquia announcement
“Presenting the 2026 State of Clinical AI Report”
"AI is already inside healthcare. Some systems measurably improve diagnosis and patient care. Many do not. This talk distils important findings from the State of Clinical AI Report,
our team's approaches building AI systems that harness primary patient datasets to directly inform advanced T cell designs optimized for clinical outcomes, with initial validation in preclinical models."
factors governing T cell function and toxicity in patients. Artificial intelligence (AI) approaches offer an exciting opportunity to tackle this problem by learning unified representations from diverse data types spanning molecular, cellular, and clinical modalities. I will provide an overview on
discovery proceeds one edit at a time, and existing preclinical models do not represent patient biology, which often results in failure upon clinical translation. Overcoming these challenges to improve patient outcomes and reduce toxicities requires a systems-level understanding of the multiscale
Abstract: "T cell immunotherapies have reshaped the treatment landscape for hematologic malignancies and are rapidly extending to solid tumors, autoimmune diseases, and transplant tolerance. Yet durable benefit remains inconsistent, and toxicities remain clinically significant. The current
Dr. Good has been named an Arthur & Sandra Irving Cancer Immunology Fellow in 2022, Parker Bridge Fellow in 2023, and an AACR-Woman in Cancer Research Scholar in 2024.
2022, 2024, Science 2021, Nature Methods 2016, 2022, and NEJM 2024), and an initial senior author papers (ICML 2025, NeurIPS 2025, Frontiers in Immunology 2025). Her research is supported by the NIH/NCI Pathway to Independence Award, NIH/OD Multimodal AI Initiative, and the Weill Cancer Hub West.
for advanced T cell therapy design. Dr. Good earned her Ph.D. in Computational & Systems Immunology from Stanford University. Her work includes 4 first-author papers (Nature Medicine 2018 & 2022, Nature Biotechnology 2019, Trends in Immunology 2019), 18+ co-authored papers (including Nature 2019,
is to understand and enhance engineered T cell immunotherapies for cancer and immune-mediated diseases through innovative computational approaches and systems immunology. Her lab leverages innovation in machine learning and clinical multiomic datasets to build artificial intelligence systems
Bio: Zinaida Good, Ph.D., is an Assistant Professor of Medicine in the Division of Immunology and Rheumatology and the Division of Computational Medicine at Stanford University. She also serves as the Director of the Stanford Center for Cancer Cell Therapy Data Hub. The goal of her research program
Zinaida Good, PhD.
@stanforddeptmed.bsky.social Biomedical Informatics Research Colloquia
“Artificial Intelligence Systems to Advance Engineered T-cell Immunotherapy Designs”
Zinaida Good, PhD.
Thursday, Jan. 8th, 2026
12 - 1 pm PST
stanford.zoom.us/j/9788759601...
Webinar ID: 978 8759 6012
Webinar Passcode: 420642
They're going to hurt others as well, because of subtle, easily missed caveats when the behavior of AI systems is so seductive. When it looks so compelling, we have to empower people to know the difference.
If you're reading this post, you're probably on the leading edge of following these topics. Realize that a lot of the community is not aware of core issues and they are going to hurt themselves.
