Sanjeev Sockalingam giving a plenary at #aadprt2020 on "Avoiding the Curriculum Carousel: Approaches to Curriculum" UIC Department of Medical Education The Wilson Centre

Big news! Our co-director Nigam Shah & teams published a groundbreaking paper on Evaluating Fair, Useful, and Reliable AI Models (FURMs) in Health Care. These open-source tools redefine AI evaluation in healthcare. Amazing work! More here: bit.ly/3Xyl6s2 #AIinHealthcare

#MentalHealth as the top health concern around the globe. Compelling data from recent survey..."Ipsos interviewed a total of 23,667 adults aged in India, Canada, Ireland, Malaysia, South Africa, Türkiye, US, Thailand, Indonesia, Singapore..." ipsos.com/sites/default/…

📢 Introducing HeadCT-ONE: Our new paper addresses a major gap in AI evaluation for radiology—capturing semantic equivalence. Using ontologies, we standardize medical terms, making AI-generated head CT reports more accurately comparable, even when phrasing differs.🧠✨

If I finetune my LM just on responses, without conditioning on instructions, what happens when I test it with an instruction? Or if I finetune my LM just to generate poems from poem titles? Either way, the LM will roughly follow new instructions! Paper: arxiv.org/pdf/2409.14254

This was a really fun project. Fine-tuning a model on "" => response produces a model that can do instruction => response What??

Our latest work improves chest x-ray report generation with LLM alignment tools! We build a scalable preference fine-tuning pipeline to improve automated metrics + expert rad. win rates—all WITHOUT any radiologist feedback. Preference alignment w/o needing human preference. 1/3

Another update to the HELM benchmarks (MMLU, Lite, AIR-Bench) with new model versions. We do see some movement near the top even with these "minor" versions updates. crfm.stanford.edu/helm/mmlu/v1.1… Claude 3.5 Sonnet (20241022) Gemini 1.5 Pro (002) Gemini 1.5 Flash (002) GPT-3.5 Turbo

Amazing turnout at the AIMI Fall Open House! Grateful to connect with & support Stanford's growing AI in health community. Highlights included opportunities to engage, vibrant discussions & a shared vision for advancing the field. Looking forward to our next community event!

We're excited to share a new paper on the AIMI Center's journey over the past 6+ years, highlighting how we built an interdisciplinary hub for AI in medicine & the core pillars guiding our work. Read more: bit.ly/4hZr92h #AIinHealthcare #StanfordAIMI

Details of the first federated learning model deployed by our friends at NASA 🛰️ between Earth and the ISS is now out! Some really cool work by Ryan T. Scott and team!

When building #ML/#genAI models, we often assume that expert-labeled data is consistent and reliable. But that’s not always the case. In radiology, for example, data labeling has a subjective component—annotations often reflect the clinician's perception rather than an objective

Learn about AI foundational models in radiology in this review article! Stanford AIMI Stanford Radiology Stanford Medicine Magda Paschali Zhihong Chen Maya Varma Louis Blankemeier Alaa Youssef Christian Bluethgen Curt Langlotz Akshay Chaudhari bit.ly/4jL4OGG

Agency > Intelligence I had this intuitively wrong for decades, I think due to a pervasive cultural veneration of intelligence, various entertainment/media, obsession with IQ etc. Agency is significantly more powerful and significantly more scarce. Are you hiring for agency? Are

🚀 We hosted an exclusive panel discussion on AI in Healthcare, featuring leading voices at the intersection of technology and life sciences! Moderated by Shiva Amiri, PhD, Partner and VP – Head of AI and Data Intelligence at Pivotal Life Sciences, the panel brought together:

What an extraordinary day & a half at the AIMI Symposium & inaugural Pediatric Symposium! Thank you to all speakers & participants for pivotal discussions. We look forward to seeing you at our future meetings! #AIMI25 #StanfordHealthAIWeek

Google introduces Test-Time Diffusion Deep Researcher Don't sleep on diffusion models. Test-Time Diffusion Deep Researcher (TTD-DR) is a deep research agent that models research writing as a diffusion process. Instead of static reasoning or bolted-on tools, the system drafts

Strong kick-off Stanford AIMI of the Inaugural AIMI AcademicxIndustry Summit 2025 on a nice fall morning Curt Langlotz #StanfordFacultyClub Stanford AIMI

1/ AI Investment Boom 🤖 Big Tech is embarking on an epic AI data center buildout, with capital expenditures of ~$400 billion this year and trillions more on the way.

McKinsey just dropped its 2025 AI report. 1. Everyone’s testing, few are scaling. 88% of companies now use AI somewhere. Only 33% have scaled it beyond pilots. 2. The profit gap is huge. Just 6% see real EBIT impact. Most are still stuck in “experiments,” not execution. 3. The