Good news! CPH's @amalaa.bsky.social and colleagues @roxanadaneshjou.bsky.social and Tom Harvitgsen have received a grant from the NIH Director's office for work on participatory mutimodal AI and editable foundation models to improve diagnosis and tx. @stanforddeptmed.bsky.social

What happens in SAIL 2025 stays in SAIL 2025 -- except for these anonymized hot takes! 🔥 Jotted down 17 de-identified quotes on AI and medicine from medical executives, journal editors, and academics in off-the-record discussions in Puerto Rico

irenechen.net/sail2025/

Real world data (RWD) analyses need diverse expertise in medicine/stats/causality. As a result, RWD causal analysis is slow and prone to error. AI tools can help.

Perspective in NEJM AI w/Maya Petersen, @amalaa.bsky.social, Chris Holmes, Mark van der Laan

ai.nejm.org/stoken/defau...

Fourth lecture of CPH 290: Julia Adler-Milstein provided an overview of the Division of Clinical Informatics and Transformation at UCSF and their approach for deploying and evaluating AI models within the health system.

youtu.be/lBMPJ8R3Zd4?...

If you're attending #NeurIPS2024 be sure to stop by our lab's posters today!

In Poster Session 3 (11 AM - 2 PM PST), Frances Dean will present our work on learning physics-based models of cardiac hemodynamics using non-invasive data to simulate disease and treatment outcomes.

In our third CPH 290 lecture, we hosted the CTO and co-founder of OpenEvidence, one of the most widely used AI-based medical search platforms. He shared how his team uses LLMs + other tools to enhance the visualization, presentation and synthesis of clinical evidence.

youtu.be/8-ui5UsD5OU?...

I'm recruiting PhD students for Fall 2025! CS PhD Deadline: Dec. 15th.

I work on safe/reliable ML and causal inference, motivated by healthcare applications.

Beyond myself, Johns Hopkins has a rich community of folks doing similar work. Come join us!

Probably should be making pies, but it’s much more fun to blog about calibration.

This one gets into more practical issues w/recently proposed solutions like multicalibration, discussing results from a recent empirical evaluation

statmodeling.stat.columbia.edu/2024/11/26/p...

In the second lecture of CPH 290, @jameszou.bsky.social gave an overview of the evaluation practices and regulatory landscape of medical AI. We posted the lecture on Youtube:

youtu.be/f8wr_Md6xnk?...

It's tough to gain visibility as a young researcher, and it's job market season! Are you a theoretical computer science PhD/postdoc on the job market?

I don't have a crazy juge audience but I'll try to help a bit: fill this form, and I'll tweet your pitch and info!
docs.google.com/forms/d/e/1F...

Most clinical AI models are only evaluated for accuracy in retrospective datasets w/o real-world evaluation of clinical utility. In the the first lecture of our CPH 290 class, Julian Hong (UCSF) discussed a UCSF RCT of AI-driven risk prediction in radiotherapy acute care.

youtu.be/GAf4yc61gv8?...

Hello BlueSky world! 🦋 We're recruiting PhD students at UC Berkeley and UCSF!

If you're interested in machine learning for healthcare, statistics/causal inference, or medical vision-language models, we'd love to hear from you: docs.google.com/forms/d/e/1F...