EP16 Dr. Fei Wang, PhD
From Prediction to Prevention: Temporal AI and Fairness in Emergency Medicine
Guest: Dr. Fei Wang, PhD
Professor of Population Health Sciences and Emergency Medicine, Associate Dean for AI and Data Science, Weill Cornell Medicine
Release Date: October 12, 2025
Episode Summary:
Can artificial intelligence predict when your emergency department will be overwhelmed—and help prevent it?
In this episode of the STAT AI Podcast, Drs. DJ Apakama and Ethan Abbott sit down with Dr. Fei Wang of Weill Cornell Medicine to explore how temporal AI and fairness-driven algorithms are changing the way clinicians anticipate and manage patient care.
Dr. Wang, a global leader in clinical machine learning, shares how temporal modeling can reveal hidden patterns in disease progression, identify subtypes of conditions like sepsis, and guide more precise and timely treatment decisions. He explains how AI systems trained to recognize evolving trajectories can shift emergency medicine from reacting to crises toward preventing them altogether.
The conversation also takes on the challenge of equity in healthcare AI. Dr. Wang describes how bias can emerge from uneven data and why continuous monitoring, transparency, and human-in-the-loop oversight are critical to ensuring AI tools work for every patient.
Finally, the group discusses how predictive models can forecast emergency department overcrowding hours in advance, helping clinical teams prepare resources, adjust staffing, and improve patient flow. Dr. Wang also offers practical advice for smaller and rural hospitals on safely piloting AI projects through federated learning and shared data governance.
This episode provides a thoughtful and pragmatic look at how AI can help emergency medicine evolve from prediction to prevention—making care smarter, fairer, and more responsive for patients everywhere.
In This Episode, We Cover:
🚦 How AI models can forecast ED overcrowding hours in advance to enable proactive resource allocation.
🧭 Why temporal AI is key to understanding how sepsis and other critical conditions evolve over time.
⚖️ Designing AI systems that preserve fairness across patient groups and reduce algorithmic bias.
🏥 Building trust through human-in-the-loop systems that augment clinicians instead of replacing them.
🤝 How community and rural hospitals can run lean, safe AI pilots using federated learning and shared governance.
🔄 Turning prediction into prevention: the path from academic research to equitable clinical deployment.
Papers Discussed This Episode:
Connect with the Guest:
Weill Cornell Medicine, Department of Population Health Sciences and Emergency Medicine
Dr. Fei Wang, PhD (University Profile & Linkedin)
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Tags: #AIinHealthcare #EmergencyMedicine #ClinicalAI #DigitalHealth #FairnessInAI
