Superb tweet chain by Jason Alan Fries reg the work on medalign.stanford.edu and why it matters. Check out the series 👇

Excited to be in Vancouver 🇨🇦 for #AAAI24 with Scott Fleming to present:

'MedAlign: A Clinician-Generated Benchmark Dataset for Instruction Following with Electronic Medical Records'

If you are interested in healthcare LLMs and preference alignment, checkout our talk and…

It was fun to summarize lessons learned from research in partnership with Stanford HAI, Center for Research on Foundation Models, Stanford Medicine for our clinical colleagues. We have to verify the claimed value propositions (hai.stanford.edu/news/how-found…) because they don't always pan out (hai.stanford.edu/news/how-well-…)!

Thank you Katie Link for sharing this work. In the spirit of the HELM project, crfm.stanford.edu/helm/latest/ Stanford HAI it would be amazing to get more focus on the need of 'evaluations that matter' rather than 'evaluations we can do'!

You have probably heard of #chatGPT , which is a class of models called 'large language models' or Foundation Models .. what else could such models be useful for? Check out below ..

Come present your work at SAIL 2023 - Rio Grande, Puerto Rico from May 9th to 12th.

Call for abstracts and travel support applications will be open until January 20th.

sail.health/call_for_paper…

#StanfordAIHealth is almost here! Join us Dec 6-7 to explore critical & emerging issues related to AI's impact across the spectrum of healthcare. Stellar program with talks, panels, firesides & live Q&A. 9 CME credits. Register: aihealth2022.stanford.edu Stanford HAI Stanford CME

“As a community, I think we’re hung up on the performance of the model and not asking the question, is the model useful? We need to think outside the model.” Nigam Shah, Chief Data Scientist for Stanford Health Care. stanford.io/3NXiKNk

Very thoughtful analysis Stanford Department of Medicine by Agata Foryciarz 🇺🇦, Stephen Pfohl, Birju Patel on the interaction between imposing fairness constraints and practice guideline adherence. Good example of our holistic view at Stanford Medicine as suggested by Stanford HAI

Join us May 24 for AIMI Symposium 2022 as we convene in person & online to discuss key advances and future vision for AI in medicine: scientific understanding of disease, clinical applications, delivery science, open data & ethics. Register: stanford.io/3v4z86z #AIMI22

Superb signout by Stephen Pfohl! His is one of 179 papers accepted out of 711, completing his trilogy scholar.google.com/citations?view…, scholar.google.com/citations?view…, scholar.google.com/citations?view… on #algorithmic #fairness Stanford Medicine and Stanford HAI

Looking forward to the fun event by Karandeep Singh Yin Aphinyanaphongs on Nov 18th NYU Langone Health!

Join us THIS AFTERNOON for an amazing #AMIA2021 panel!

A new platform at Stanford AIMI offers datasets at no cost, with the aim of spurring crowd-sourced AI applications in healthcare. stanford.io/3mKhm4p

Our new correspondence piece in Nature Medicine, led by Viknesh Sounderajah, discusses a quality assessment tool for AI-centered diagnostic test accuracy studies nature.com/articles/s4159… 🔓

This new tool will provide a specific framework
to evaluate risk of bias & applicability

Results in NEJM Catalyst article, catalyst.nejm.org/doi/full/10.10….

Assessing the Future of #PublicHealth Data Exchange, #Interoperability ehrintelligence.com/news/assessing…
“We need to rethink public health data [as a] fundamental construct,” Donald Rucker said.
This involves shifting a mandated reporting mindset to a data reuse framework, he explained.

Thank you National Library of Medicine for supporting the #DataScience that led to the results in NEJM Catalyst. Nice example of how #informatics to drive innovations in #DigitalHealth delivery Stanford Health Care via a diverse team of Alison Callahan Saurabh Gombar Keith Morse Eli Cahan Robert Harrington + others!

Nice summary Jonathan Lu's work by Stanford HAI “Flying in the Dark”: Hospital AI Tools Aren’t Well Documented hai.stanford.edu/news/flying-da…

Do ML models with better AUC performance necessarily have higher utility?🤔

Our new paper assesses utility of ML models for allocating interventions to avoid unplanned readmissions.

Led by Michael Ko & Emma Chen Ashwin Agrawal w/ Nigam Shah et al.

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sciencedirect.com/science/articl…