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📢I am on the industry and academic job market this year! My goal is to enable human-AI teams to solve real-world tasks. I bring a unique skill set that combines ML, HCI, and domain knowledge in healthcare. Please reach out if you have any opportunity that would be a good fit!

For medical knowledge tasks, some think that for best results you need fine-tuning and prompts crafted by human medical experts . But no! This study Microsoft Research & Eric Horvitz shows that generalist #GPT4 beats specialized models *and* is less expensive. microsoft.com/en-us/research…

AI has uncovered new insights from medical data like disease risk & severity, transforming our understanding of health. But what if AI performance is worse than a human's? Start thinking differently, says #JameelClinic PI David Sontag to ProfDhar on Brave New World podcast 🎧

Mike finished his Ph.D. with me at MIT a year ago, and is now recruiting students in CS Johns Hopkins University. Consider applying to work with him - he's a great mentor and top researcher.

Monica finished her Ph.D. with me at MIT a year ago and is starting a research group at Duke in Sept 2024. As a leader both in industry Layer Health and in academia, her LLM work is transforming healthcare. Consider applying to Duke CompSci and DukeBiostats

Our NeurIPS '23 paper by Hussein Mozannar and colleagues at MIT-IBM Watson AI Lab featured on MIT homepage today. Article here -- news.mit.edu/2023/automated…

We're excited to introduce #INSPECT a large-scale ✨3D multimodal✨medical imaging dataset #NeurIPS2023 19,402 Stanford Medicine Patients 🩻23,248 CT Scans + 📄Paired Radiology Notes 📈Longitudinal EHRs 🩺Clinician-validated task labels #DataCentricAI #Multimodal #3Dimaging 1/

a hype-free, sober conversation on AI for healthcare by ProfDhar with David Sontag at open.spotify.com/episode/75JIST…

In my The Boston Globe Op-Ed today, I urge the US government and philanthropists to ensure that Americans can benefit from repurposed generic drugs: bostonglobe.com/2023/12/27/opi…. Reboot Rx #RebootRx #TheSolutionMayAlreadyExist #cancer #drugrepurposing #nonprofit

Help us evaluate how well code LLM models assist humans in completing coding tasks! Register interest in our online 35 min Python study with $15 compensation forms.gle/BHwJf2b2bp4f4d… it also serves as paid LeetCode practice!

How do LLMs like #ChatGPT impact clinical note readability? LLM augmentations enhance understanding (from user study with 207 participants- 17% increase in understanding for augmentations vs control, p=0.002), but validation was needed to avoid errors: arxiv.org/abs/2401.09637

Learning to Decode Collaboratively with Multiple Language Models We propose a method to teach multiple large language models (LLM) to collaborate by interleaving their generations at the token level. We model the decision of which LLM generates the next token as a latent

Thanks AK for tweeting our work! 🤝Co-LLM trains a language model to collaboratively decode with other LMs. It decides whether to invoke the other assistant LM for each token. By optimally combining the expertise from each LM, co-llm generation can be better than using

Co-LLM can help achieve better performance than using a single model alone. We experimented with co-llm generations at different frequencies for invoking the assistant model, and visualized the generations.

Congratulations to Dr. Hussein Mozannar. Hussein Mozannar Strong dissertation research exploring multiple dimensions of human-AI collaboration. David Sontag Elena Glassman Arvind Satyanarayan Massachusetts Institute of Technology (MIT)

So happy to defend my PhD thesis and couldn't have done it without a 1 of 1 advisor David Sontag and an incredible committee Eric Horvitz Arvind Satyanarayan Elena Glassman

What personalized cancer treatment options are there when clinical trials aren't able to test every patient scenario? Zeshan Hussain, Barbara Lam, Fernando Acosta-Perez, Irbaz Riaz MD,MS,MBI,PhD, Maia Jacobs, Andrew Yee, MD, and #JClinic PI David Sontag propose a ML-based approach arxiv.org/pdf/2404.15187

Excited to present our work at #ICML2024, “Prediction-powered Generalization of Causal Inferences.” Limited external validity of randomized controlled trials (RCT) is a big challenge to causal inference. We investigate how integrating data from observational studies (OS) can

No two cases of multiple myeloma are alike, making treatment decisions a challenge. In npj Digital Medicine, ASPIRE awardee David Sontag introduces a machine-learning model to help physicians estimate disease progression & treatment outcomes. #PrecisionMedicine

New preprint dropped! Times have changed since the IDSA released tx guidelines for uncomplicated UTI in 2010. We looked at a large claims database formatted into the OMOP common data model to see if the recommendations still hold. tl;dr They do 1/7 medrxiv.org/content/10.110…