Aidoc Releases BRIDGE: A New Industry Framework to Guide Safe, Scalable Clinical AI Deployment

Authored by 17 experts across healthcare, academia, and technology, BRIDGE offers an open framework for turning AI ideas into real-world clinical solutions.

Introduction

At HLTH Europe, Aidoc announced the release of BRIDGE, a new open-source framework developed to help healthcare organizations deploy AI safely, effectively, and at scale. Developed by Aidoc in collaboration with NVIDIA, the BRIDGE framework reflects the combined insights of health systems, clinicians, and technology leaders working at the front lines of AI adoption.

Short for Blueprint for Resilient Integration and Deployment of Guided Excellence, the framework outlines the technical, regulatory, operational, and trust-building criteria AI solutions must meet to be considered healthcare-ready. Developed with input from 17 leading organizations, including the University of Washington, University Hospitals, and Ochsner Health, it offers a practical, implementation-focused roadmap for hospitals navigating the complexities of clinical AI deployment.

Framework Overview

"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. "BRIDGE provides that structure. It helps the industry align on what 'good' looks like so we can accelerate adoption without compromising safety or performance."

As clinical AI adoption accelerates, there's a growing opportunity to align around a shared framework that supports consistent, scalable, and trusted deployment. BRIDGE was created to address that need, offering a common set of expectations for what it takes to move from experimentation to real-world integration.

Key Components

A lack of shared definitions and deployment expectations has led to fragmentation across vendors, evaluation processes, and hospital IT strategies. BRIDGE aims to unify that environment by providing CIOs, governance leaders, and platform vendors with a clear, consensus-driven foundation for assessing and integrating AI solutions.

"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 of medicine and collaborative intelligence at the University of Washington.

Core Areas of the Framework

The BRIDGE framework is structured around core areas that determine whether clinical AI can function safely and effectively in real-world settings. These include:

• Clear distinction between models and full solutions
• Minimum viable production environment (MVPE) requirements
• Trust-building mechanisms
• Scalability guidelines

Together, these components form a unified structure for evaluating, purchasing, and deploying AI solutions. BRIDGE is not a vendor specification but a community-aligned framework designed to evolve over time.

HONESTAI ANALYSIS

"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 in the Department of Radiology at University Hospitals. "BRIDGE gives health systems the foundation they need to scale AI responsibly and the language to do it together."

BRIDGE is built for a fast-moving field. As clinical AI advances, the framework will continue to evolve from incorporating new technologies and regulatory changes to sharing new real-world insights. From the beginning, BRIDGE has been a collaborative effort shaped by leaders across healthcare, research, and technology.

BRIDGE is now publicly available and can be downloaded for free. To learn more, contribute ideas, or get involved in future iterations, visit the site and join the community shaping the future of clinical AI.

About Aidoc: Aidoc is the leading provider of clinical AI solutions, helping health systems reduce diagnostic errors and deliver faster, more accurate care.