Translational Integration AI Showcase
In this session we address the critical challenge of translating artificial intelligence from research environments to practical clinical application. The presentation will feature a live demonstration of an integrated platform for efficiently building and deploying AI tools using real-world medical imaging data. The demonstration will cover the entire development lifecycle, beginning with data importation and labeling and proceeding through model development, testing, validation, and publication. Throughout the session, we present flexible paradigms that accommodate various levels of coding expertise among healthcare professionals. Ultimately, the goal of the session is to provide a practical framework, highlighting the key considerations for translating AI research into robust clinical solutions that enhance diagnostics and improve patient care.
Objectives
Identify the primary barriers to implementing research-grade AI models within active clinical workflows
Demonstrate an end-to-end development cycle for creating a medical imaging AI algorithm
Explore tools that enable users with varying technical skills to build, validate, and deploy AI models
Discuss practical opportunities to leverage custom AI for enhancing diagnostic precision and operational efficiency in their own practice.
Sponsored by
Speakers
Peter Chang, MD
Associate Professor, Departments of Radiological Sciences and Computer Science, University of California, Irvine
Director, UCI Center for AI in Diagnostic Medicine