MLHC is coming to Baltimore! Mark your calendars for August 13-14, 2026. Follow for spotlights, practical author tips, and timely updates. #MLHC2026 #AIinMedicine #AIML #Healthcare

From Baltimore to Zurich 🇺🇸✈️🇨🇭 We still have more #MLHC2026 research and moments to share, but we’re already looking ahead. Our next stop is @ETH Zürich for #MLHC27, August 11–13, 2027. Save the date. We can’t wait to see you in Switzerland!

That’s all, folks. 🫡 #MLHC2026 is officially in the books. We hope you learned a lot, had some fun, made a few new friends (and collaborators), and leave Baltimore with your head full of ideas. Get home safe. Get some sleep. See you at #MLHC27

Equity shouldn’t be a post-processing step. Emma Pierson takes the #MLHC2026 stage on using machine learning not just to predict outcomes, but to understand disparities, support scientific discovery, and help build more equitable healthcare and public health.

C is for crowded. Poster Session C is in full swing at #MLHC2026, with another packed hallway of new work, new ideas, and conversations spilling well beyond the poster boards.

Foundation models, virtual patients, and a dose of “okay, but does it actually work?” Anna Goldenberg and Hoifung Poon bring the morning’s ideas together, moderated by Mike Hughes at #MLHC2026.

From screening image to five-year risk prediction. Yuxuan Chen, Yanqi Xu, Laura Heacock, Linda Moy, Yiqiu Shen & Alana Lewin bring deep learning to screening breast ultrasound at #MLHC2026, exploring whether the images contain risk information beyond what we use clinically today

2016: recurrent neural networks for predicting clinical events. 2026: the first-ever MLHC Test of Time Award. 🏆 A decade later, we’re celebrating Doctor AI and the lasting impact of work by Choi, Bahadori, Schuetz, Stewart, and Sun. #MLHC2026

Poster Session B is packed. 🔬 Another round of new work, crowded aisles, and the kind of conversations that are hard to fit into a 36 × 48 inch poster. #MLHC2026

Teaching the model when to raise the alarm, even when the data don’t stick around for the ending. 🚨 Qin Weng presents censoring-aware reinforcement learning for early clinical risk alerts at #MLHC2026, with Goldstein and Engelhard.

When you can’t observe the confounder, sensitivity analysis has to do some heavy lifting. Agathe Guilloux takes the #MLHC2026 stage with a doubly valid, doubly sharp approach for survival outcomes, joint work with Baitairian, Sebastien, Jreich, and Katsahian.

Obed Dzikunu presents work @ #MLHC2026 on learning prostate anatomy at test time for cancer detection in micro-ultrasound, with Abootorabi, Harmanani, Wilson, Willis, Luger, Kinnaird, Wodlinger, Mousavi & Abolmaesumi

Dongkyu Cho presents Tree of Concepts at #MLHC2026, joint work with Xiyue Li, Samrachana Adhikari, and Rumi Chunara, bringing interpretability to models learning in non-stationary clinical environments.

Some of the data are missing. Ilya Shpitser has thoughts about that. Now at #MLHC2026: causal inference, missing-not-at-random data, and what it takes to impute responsibly when the missingness itself is part of the problem.

From promising AI to actually making it work in healthcare @rahulgk, @HealthcareSeema, @SaraMurrayMD, and Deanna Hanisch take the stage for the #MLHC2026 fireside chat, bringing perspectives from clinical care, health system leadership, informatics, and healthcare technology

Poster session A is officially in full swing at #MLHC2026 🔬👀 Packed aisles, packed boards, and a lot of very good conversations happening in Baltimore.