Emily Alsentzer

483 posts

Emily Alsentzer

Emily Alsentzer

@Emily_Alsentzer

Assistant Professor @Stanford in Biomedical Data Science and (by courtesy) CS. Trustworthy, deployable ML for healthcare. Prev @HarvardMed @mit_hst @MIT_CSAIL.

Palo Alto, CA Katılım Haziran 2012
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Emily Alsentzer retweetledi
chilconference
chilconference@CHILconference·
June is going to be a busy month for Seattle 👀 CHIL, FIFA, and… 🥁 AHLI’s inaugural Health AI Summer Camp 📍 University of Washington 📅 June 22–28, 2026 Fully funded for accepted participants. ⏳Apply by April 15 (limited spots): ahli.cc/summercamp
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chilconference
chilconference@CHILconference·
The CHIL 2026 Doctoral Symposium is back! Apply by March 13th 📅 chil.ahli.cc/submit/doctora… Last year, we welcomed 28 outstanding PhD researchers for mentorship and lightning talks in health AI. Watch 3 participant talks from 2025 👇 (see 2:48:43) youtube.com/watch?v=YaDonA…
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chilconference
chilconference@CHILconference·
Help us shape the conversation at CHIL 2026! We invite suggestions for Research Roundtable topics about controversial or open questions in machine learning for healthcare. Drop your suggestions here: forms.gle/XPNddbmqaMZyv6…
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chilconference
chilconference@CHILconference·
Happy Holidays from AHLI! But first, a quick reminder: 📣 CHIL 2026 is coming to Seattle, June 28-30th. 📝 Submission site is now open! ⏰ Deadline: Feb 4, 2026 🤝 Sponsorship opportunities available 🌎 Request an invitation letter for visa applications chil.ahli.cc
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ML4H
ML4H@SymposiumML4H·
Where should we host next year's symposium? Please let us know by filling in our feedback form or commenting below: #ML4H2025
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Emily Alsentzer
Emily Alsentzer@Emily_Alsentzer·
Looking forward to @SymposiumML4H! The Alsentzer Lab just turned 1, & we’re celebrating with 4 papers on longitudinal EHR QA eval, LLMs for rare disease diagnosis, prior-chat bias in LLMs, & inference-time merging of general+clinical models. We’re recruiting postdocs-Let’s chat!
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Aishwarya Mandyam
Aishwarya Mandyam@Aishwarya_R_M·
✨I'm on the research scientist and postdoc job market! I'll be graduating from my PhD this academic year with a thesis that focuses on reinforcement learning and healthcare. ✨
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Aishwarya Mandyam
Aishwarya Mandyam@Aishwarya_R_M·
I'll also be presenting some new work at ML4H (arxiv.org/abs/2511.17818) which focuses on building synthetic datasets for off-policy evaluation in healthcare.
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DBMI at Harvard Med
DBMI at Harvard Med@HarvardDBMI·
CALL FOR ABSTRACTS | SAIL 2026 on May 5–8 in Río Grande, Puerto Rico! In-person attendance limited to those with accepted work. Apply by 1/16/26. Oral presentation invitations & @NEJM_AI-sponsored travel awards go to the top abstract submissions. #SAILhealth26 - sail.health/event/sail-202…
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Isaac Kohane
Isaac Kohane@zakkohane·
IFF you: @stanford student Want: Publish your study in NEJM AI Free: November 18th at noon PST DO: contact me at pitchme@zaklab.org Me: Buy you coffee/refreshment while you pitch the study.
Isaac Kohane@zakkohane

Pitch @NEJM_AI your manuscript in a Palo Alto café near @Stanford IFF you are a student. I'll let you know if it's interesting (or would desk reject as fast as I can hit send). I have time for 12 pitches so contact pitchme@zaklab.org if you are available Nov 18 at noon PST. Coffee is on me. Review our website to get an idea of content of interest.

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chilconference
chilconference@CHILconference·
📣 Announcing the 7th Annual Conference on Health, Inference, and Learning (CHIL) happening June 28-30, 2026 in Seattle, WA! 👉 Call for Papers is up at chil.ahli.cc/submit/call-... ⏳ Submit by February 4, 2026
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Alyssa Unell
Alyssa Unell@AlyssaUnell·
Super excited that our work with TIMER has been published in npj Digital Medicine! We explore the role of temporal bias in both clinician and synthetically generated data-- showing current benchmarks don't evaluate models across the full input context of a patient's record.
Alyssa Unell@AlyssaUnell

1/🧵Introducing TIMER: Temporal Instruction Modeling and Evaluation for Longitudinal Clinical Records When we evaluate LLMs for reasoning over longitudinal clinical records, can we leverage synthetic data generation to create scalable benchmarks and improve model performance?

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Divya Shanmugam
Divya Shanmugam@dmshanmugam·
I am on the job market this year! My research advances methods for reliable machine learning from real-world data, with a focus on healthcare. Happy to chat if this is of interest to you or your department/team.
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Irene Chen
Irene Chen@irenetrampoline·
Traditional ML fairness audits don't work in the LLM era, eg medical LLMs may have eq treatment rec rates across groups (seemingly good!) but differ in empathetic vs dismissive phrasing (bad!). Also what do "groups" even mean now? New NEJM AI piece w @Emily_Alsentzer out today
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Emily Alsentzer
Emily Alsentzer@Emily_Alsentzer·
We show how to apply these guidelines to two deployed use cases: • Drafting replies to patient messages • Mental health chatbots Full paper: doi.org/10.1056/AIp250… Had a great time collaborating with the incredible @irenetrampoline on this!
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Emily Alsentzer
Emily Alsentzer@Emily_Alsentzer·
We need: • Clearer ways to define at-risk groups (e.g., looking beyond explicit demographics to groups inferred from input text) • More comprehensive metrics (e.g., factuality, thoroughness, tone, tailoring to context, and stigmatization)
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Emily Alsentzer
Emily Alsentzer@Emily_Alsentzer·
🚨 LLMs are rapidly entering the clinic - ambient documentation tools are now deployed at most major hospital systems, and Epic alone has dozens of LLM applications in development. Yet we lack systematic ways to evaluate these *already deployed models* for bias. 🧵
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Keşfet

@SymposiumML4H @NEJM_AI @Stanford @PierreEliasMD @irenetrampoline @elonmusk @BarackObama @taylorswift13