How can we diagnose what we haven’t yet defined? Nicole welcomes Dr. Shamim Nemati and Dr. Gabriel Wardi to explore how artificial intelligence (AI) is reshaping sepsis detection. They dig into why existing definitions fall short, how data-driven tools can outperform traditional alerts, and where AI could take us next, from smarter antimicrobial stewardship to real-time clinical support. A conversation for anyone rethinking how we recognize and respond to sepsis.

Featured Guests:

Gabriel Wardi, MD, MPH, FACEP ( @WardiGabriel on X): Emergency medicine and critical care physician at UC San Diego focused on improving sepsis pathways, triage systems, and early intervention in acute care.

Shamim Nemati, PhD (@ShamimNemati on X): Biomedical informatics researcher and AI scientist specializing in predictive analytics, machine learning, and sepsis risk modeling in real-time clinical settings.

Key Takeaways:

Clarify how artificial intelligence, machine learning, and traditional decision tools differ and how each is evolving to improve sepsis detection and antimicrobial stewardship.

Explore how cutting-edge AI/ML models are helping close gaps in infection prevention, early sepsis detection, diagnostics, and resistance forecasting.

Learn how these tools are being applied to risk prediction, therapy selection, and alert refinement across hospital workflows.

Walk away with real-world examples and design insights to help improve diagnostic precision and clinical decision support in your own system.

—

Get in Touch: [email protected]

Or Visit Us At: SepsisPodcast.org

Connect with Nicole on Socials: @nicolekupchik

Connect with Sepsis Alliance on Socials: @sepsisalliance

To Learn More About Sepsis, Visit EndSuperbugs.org

Produced by: Human Content and Sepsis Alliance