activity
20242026
collaborators

9 papers

cs.AI2026

ResidencyRL: Reinforcement Learning in Simulated Clinical Environments

Valentin Liévin, Samuel Schmidgall, Tim Strother +32

In medical education, physicians convert academic knowledge into clinical expertise through residency: years of training across thousands of encounters, with diverse sources of fee…

cs.AI202635 cited

MedGemma Technical Report

Andrew Sellergren, Sahar Kazemzadeh, Tiam Jaroensri +78

Artificial intelligence (AI) has significant potential in healthcare applications, but its training and deployment faces challenges due to healthcare's diverse data, complex tasks,…

cs.CV2026

Decoding Visual Experience and Mapping Semantics through Whole-Brain Analysis Using fMRI Foundation Models

Yanchen Wang, Adam Turnbull, Tiange Xiang +6

Neural decoding, the process of understanding how brain activity corresponds to different stimuli, has been a primary objective in cognitive sciences. Over the past three decades,…

cs.AI2025

TxGemma: Efficient and Agentic LLMs for Therapeutics

Eric Wang, Samuel Schmidgall, Paul F. Jaeger +6

Therapeutic development is a costly and high-risk endeavor that is often plagued by high failure rates. To address this, we introduce TxGemma, a suite of efficient, generalist larg…

cs.LG2024

Health AI Developer Foundations

Atilla P. Kiraly, Sebastien Baur, Kenneth Philbrick +23

Robust medical Machine Learning (ML) models have the potential to revolutionize healthcare by accelerating clinical research, improving workflows and outcomes, and producing novel…

cs.CY2024

A Toolbox for Surfacing Health Equity Harms and Biases in Large Language Models

Stephen R. Pfohl, Heather Cole-Lewis, Rory Sayres +27

Large language models (LLMs) hold promise to serve complex health information needs but also have the potential to introduce harm and exacerbate health disparities. Reliably evalua…