UT-HIP joined clinicians, health systems, researchers, builders, investors, policymakers, and industry leaders at the UT REAL Health AI (RHAI) Symposium, held October 7-8, 2026, in Austin, Texas. Together, participants explored a shared question: how can health AI earn trust, adoption, and scale?
Our team contributed six presentations across two days: one main-stage session, three breakout sessions, and two posters. These sessions highlighted the connections between data, AI, and collaboration, with topics ranging from identifying clinical information in patient notes to supporting rural health and exploring pathways to care.
Main-Stage and Breakout Highlights
On the main stage, ShuRon Green and Claus Jensen shared “REAL Health AI: Progress and Priorities, UT-HIP and Data and AI Ecosystem.” Our breakout sessions continued the conversation: Xiaoqian Jiang presented “AI for Rural Health: Connecting the Point of Care to the Point of Need,” and ShuRon Green, Raghu Kolli, Ramesh Pandey, and Patrick Boswell led “Deeper Dive: AIMS, Model Monitoring, and the UT-HIP Data & AI Ecosystem.”
UT-HIP Quality Collaborative: Hidden in the Notes
Our UT-HIP Quality Collaborative shared “Hidden in the Notes: LLMs for Identifying Altered Mental Status in Sepsis” through both a breakout session and a poster. Gustavo Villarreal and Alyssa Hughes presented the breakout session, highlighting the use of large language models to identify altered mental status in clinical notes for patients with sepsis.
UT-HIP Rural Health Collaborative: From Prediction to Access
Our UT-HIP Rural Health Collaborative presented the poster “From Prediction to Access: A Human-Supervised AI Workflow for Ambulatory No-Show Reduction.” The poster highlighted a workflow focused on reducing missed ambulatory appointments with human oversight, connecting AI development with practical healthcare needs.
UT-HIP In Action
Our participation in this year’s symposium reflected UT-HIP’s role in bringing the University of Texas System’s mission, talent, and capabilities together to advance data-driven improvements, discovery, and innovation. This work reaches beyond any single project: we are building a collaborative ecosystem where each insight informs the next discovery and strengthens the future of health intelligence across Texas. We look forward to growing this ecosystem together and invite our partners to help shape that future with us.
