Lab profile
About IC3
IC3 is a collaborative research partnership bringing together experts in Medicine, Health Policy Research, and Computer Engineering to develop and refine data analysis methods using modern approaches to modeling, signal processing, and machine learning. The center focuses on developing trustworthy artificial intelligence technologies for critical care, creating predictive models, physiologic markers, and clinical reasoning tools to improve patient care in intensive care and preoperative environments.
01 · Research focus
Research areas and highlights
Topics and recent work as stated on the lab’s own site.
- CHoRUS (Bridge2AI)A multimillion dollar collaboration creating a 100,000 patient dataset with ethical standards for AI in critical care research and education.
- Intelligent Intensive Care Unit (I2CU)Develops deep learning models for autonomous, precise, and interpretable patient condition assessment to enhance clinical workflow and early intervention.
- ADAPTAutonomous Delirium Monitoring and Adaptive Prevention system that quantifies delirium indicators and predicts trajectories to prompt risk-reducing actions.
- DREAMSDigital Rehabilitation Environment Augmenting Medical System researching immersive digital reality to reduce cognitive, behavioral, and emotional consequences of critical illness.
- Autonomous Pain RecognitionDevelops algorithms that autonomously assess facial pain expressions and patient activity to quantify pain in non-verbal and critically ill patients.
- AKI-EPICAutomated algorithm that identifies and communicates acute kidney injury risk to healthcare providers through real-time EHR integration.
02 · People
Leadership and researchers
People listed on the lab’s team pages, by role.
03 · Research intelligence
Research Intelligence evidence
Publications, grants and clinical trials linked to the lab’s researchers in Health AI Central’s research data.
Publications & preprints
- Matching Surgical Datasets to Prediction Tasks: NSQIP and Non-NSQIP Artificial Intelligence Models Across Specialties.Journal of the American College of Surgeons · 2026
- Development and External Validation of a Machine Learning-Based Simplified Injury Severity Score for Improved Trauma Mortality Prediction.Journal of the American College of Surgeons · 2026
- Emotional responses to naturalistic and artificial intelligence (AI)-generated affective pictures: A systematic comparison.Emotion (Washington, D.C.) · 2026
Active NIH grants
- Artificial Intelligence Passport for Biomedical Research: Digital Experiential Learning Community for Upskilling in Artificial Intelligence for Biomedical, Behavioral and Clinical ResearchAzra Bihorac · NIGMS · FY 2026
- Computational Imaging of Renal Structures for Diagnosing Diabetic Nephropathy.Pinaki Sarder · NIDDK · FY 2026
- Computational Image Analysis of Renal Transplant Biopsies to Predict Graft OutcomePinaki Sarder · NIDDK · FY 2026
04 · Updates
Updates and lab news
News and events from the lab’s own site.
- Dr. Azra Bihorac Named Distinguished ProfessorAwardJul 23, 2026
- In a New Dawn of Clinical AI, the Biggest Gift is…NewsMar 6, 2026 · ic3.center.ufl.edu
- AI Social Event: Machine LearningEventNov 12, 2025
- Visiting Professor Dr. Mathieu KomorowskiEventOct 16, 2025
- AI Collaboratory HubEventOct 8, 2025 · ic3.center.ufl.edu
- AI4Health Journal ClubEventAug 27, 2025
- IC3 in the News – AI in Biodiversity SymposiumNewsAug 15, 2025 · ic3.center.ufl.edu
- UF's innovative AI research on Intelligent…NewsDec 11, 2024 · ic3.center.ufl.edu
05 · Official presence
Lab sources and channels
The lab’s own pages and accounts.
06 · Related
Related labs and centers
Labs at the same institution and labs working on similar topics.