Aidoc introduced BRIDGE, an open-source framework designed to guide healthcare organizations in deploying clinical AI safely and effectively. Developed in collaboration with NVIDIA and 17 leading organizations, including the University of Washington and Ochsner Health, BRIDGE provides a structured approach to integrating AI solutions into real-world clinical settings.
Aidoc launches BRIDGE framework at HLTH Europe 2025 for clinical AI.
Developed with NVIDIA and 17 healthcare and tech organizations.
Focuses on technical, regulatory, and trust-building standards for AI.
Offers scalability guidelines for seamless AI integration in hospitals.
Free to download at www.aibridgeframework.com for community use.
Aims to unify AI deployment with a consensus-driven roadmap.
The BRIDGE framework, short for Blueprint for Resilient Integration and Deployment of Guided Excellence, was crafted with input from health systems, clinicians, and technology leaders. It addresses the need for a unified structure to ensure safe and scalable AI deployment in healthcare. "To safely deploy AI in healthcare, we need more than strong algorithms. We need shared structure," said Reut Yalon, PhD, Chief Product Officer at Aidoc. The framework sets clear expectations for technical performance, regulatory compliance, and operational readiness, helping hospitals move from AI experimentation to impactful integration.
BRIDGE outlines critical criteria for healthcare-ready AI solutions. It emphasizes a clear distinction between standalone algorithms and complete solutions, requiring robust infrastructure and workflow integration. The framework defines Minimum Viable Production Environment (MVPE) requirements, including validation protocols and cost benchmarks. It also prioritizes trust-building through transparency and explainability, ensuring AI outputs are defensible across diverse clinical settings. Scalability guidelines address interoperability and long-term performance monitoring, enabling seamless coordination across departments.
"Deploying AI at scale requires more than technical performance. It requires trust, transparency and system-level readiness," said Efstathia Andrikopoulou, MD, echocardiography medical director at Harborview Medical Center and associate professor at the University of Washington. BRIDGE provides a practical roadmap for hospitals, addressing fragmentation in vendor solutions and hospital IT strategies. It supports CIOs and governance leaders in evaluating and integrating AI, fostering trust and ensuring long-term impact.
BRIDGE is designed to evolve with the fast-paced clinical AI landscape, incorporating new technologies and regulatory changes. "We're at a point where AI in healthcare must mature from experimentation to integration," said Leonardo Kayat Bittencourt, MD, PhD, vice chair of innovation at University Hospitals. The framework is freely available at www.aibridgeframework.com, encouraging healthcare leaders to contribute to its ongoing development. This collaborative approach ensures BRIDGE remains a dynamic tool for aligning AI creators, implementers, and decision-makers.
Aidoc’s BRIDGE framework marks a significant step toward standardizing clinical AI deployment, offering healthcare organizations a clear, consensus-driven path to safe and scalable integration. By fostering collaboration and transparency, BRIDGE paves the way for AI to transform healthcare delivery responsibly.
Aidoc is the leading provider of clinical AI solutions, helping health systems reduce diagnostic errors and deliver faster, more accurate care. Built around aiOS™, our proprietary intelligence engine, Aidoc integrates real-time insights directly into clinical workflows so care teams see what matters, when it matters most. From radiology, cardiology and beyond, we help providers close care gaps, accelerate treatment and protect the moments that matter. Used in over 1,500 hospitals and supporting 100,000 patients every day, Aidoc offers the most FDA-cleared clinical AI solutions of any dedicated AI company, setting a new standard for clarity, consistency and confidence in care.
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