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A Roadmap for Scalable, Responsible AI Adoption in Healthcare

A comprehensive framework for integrating AI into clinical practice ensuring trust, compliance and real-world impact.

AI in healthcare is advancing rapidly, but true clinical adoption lags behind. While AI models
show promise, many fail to integrate seamlessly into real-world care.

BRIDGE (Blueprint for Resilient Integration
and Deployment of Guided Excellence) is a structured, scalable and trust-driven framework designed to bridge the gap between AI innovation and clinical impact. Rooted in real-world experience, BRIDGE provides a clear roadmap for responsible AI adoption—ensuring solutions move beyond research and pilots to make a real difference in patient care.

Why This Matters

  • Move from pilot to real-world impact.

    AI shouldn’t stay in research. BRIDGE provides a proven path for implementation.

  • Trust and compliance at the core.

    Navigate evolving regulatory complexities with built-in governance.

  • Designed for scalability.

    Seamlessly integrate AI into clinical workflows for sustained adoption.

What’s Inside the BRIDGE Guideline?

  • AI Trust Framework: How to gain confidence from key decision-makers.
  • Regulatory & Compliance: Navigating FDA, CE, ISO, and beyond.
  • Real-World AI Implementation: From pilots to
scalable deployment.
  • Workflow Integration: Ensuring AI actually fits into clinical operations.
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BRIDGE in Action:
 AI That Works for Healthcare

AI solutions are more than just solutions—they need governance, validation, and seamless integration into clinical workflows. The BRIDGE framework was developed through a collaborative effort between leading AI innovators and healthcare organizations, ensuring it is practical, scalable, and aligned with real-world clinical needs.

The Collaboration Behind BRIDGE

BRIDGE was developed through a collaborative effort between AI leaders, healthcare systems, and industry partners to drive real-world AI adoption at scale.

While NVIDIA and Aidoc advanced AI infrastructure
and computing, health systems and clinical leaders ensured BRIDGE is practical, scalable, and aligned
with real-world care.

This initiative bridges the gap between AI innovation and clinical impact, moving AI beyond research into meaningful, lasting adoption.

Optimizing AI performance and computing power for real-world scalability

Advancing clinical AI infrastructure and workflow integration

Partners Penn State University, Coalition for Health AI, Radiology Partners, Cincinnati Children's Hospital and Medical Center, University Hospitals, Case Western Reserve University

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