Jonathan H Chen MD PhD

“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

YouTube video by Stanford Medicine The magic of AI in health care: Beyond the illusion | 90 Seconds w/ Lisa Kim

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.

Join our Cloud HD Video Meeting Zoom is the leader in modern enterprise cloud communications.

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.

I spoke with a community of a few hundred physicians and described many topics including how AI systems can confabulate references, and some were shocked. Shocked? That's two year old news.
edhub.ama-assn.org/jn-learning/...

Constructing the Future of Health: Stanford’s Division of Computational Medicine Stanford’s Division of Computational Medicine launches a new identity, showcasing its data-driven tools, AI innovation, and impact on clinical care.

medicine.stanford.edu/news/current...

@stanforddeptmed.bsky.social Center for Biomedical Informatics Research is now @stanfordmedicine.bsky.social Division of Computational Medicine. Reborn to reflect how computation is now central, not secondary, to shaping real medical impact.
#HealthTech #AIinMedicine #DataScience #MedTwitter

Multiple Stanford produced AI medical teaching tools to be discussed today at noon: Thursday, December 4th, 2025
12:00 to 1:00 pm PAcific

Zoom Link:
Live Stream
stanford.zoom.us/j/9788759601...
Webinar ID:
978 8759 6012
Webinar Passcode: 420642

the diagnostic process."

diagnostic accuracy. As Artificial Intelligence increasingly enters clinical practice, its potential—and its limitations—become evident: AI can support reasoning but is not immune to error either. Dr Zwaan explores how understanding both human and machine cognition can improve

Abstract: "Diagnostic decision-making is a complex interplay between intuition, analysis, and uncertainty. In this presentation, Dr. Laura Zwaan examines how clinicians reason through diagnostic challenges, the role of heuristics and cognitive bias, and why knowledge remains the cornerstone of

accuracy. Dr. Zwaan has received multiple research grants and awards, including the Mark Graber Award, in recognition of her contributions to improving diagnostic safety.