Aidoc, in collaboration with NVIDIA and insights from 17 leading experts across healthcare, academia, and technology, has unveiled BRIDGE – a groundbreaking open-source framework designed to facilitate the safe, effective, and scalable deployment of Artificial Intelligence (AI) in clinical environments. Launched at HLTH Europe, BRIDGE, which stands for Blueprint for Resilient Integration and Deployment of Guided Excellence, addresses a critical need within the rapidly evolving landscape of clinical AI adoption: the lack of shared definitions and consistent deployment expectations.

The creation of BRIDGE stems from the combined knowledge of health systems, clinicians, and technology leaders operating at the forefront of AI integration. It outlines comprehensive criteria—encompassing technical, regulatory, operational, and trust-building elements—that AI solutions must satisfy to be considered 'healthcare-ready'. This collaborative effort, with contributions from institutions like the University of Washington, University Hospitals, and Ochsner Health, provides a practical, implementation-focused roadmap to help hospitals navigate the complexities inherent in deploying clinical AI.

Reut Yalon, PhD, Chief Product Officer at Aidoc, emphasized the framework's core purpose: to provide a 'shared structure' necessary for safe AI deployment beyond just strong algorithms. BRIDGE aims to align the industry on benchmarks for 'good' AI integration, thereby accelerating adoption without compromising safety or performance. By establishing common expectations, the framework seeks to unify the currently fragmented landscape of vendor evaluations, internal hospital IT strategies, and AI solution deployment processes, offering CIOs, governance leaders, and platform vendors a clear, consensus-driven foundation.

Efstathia Andrikopoulou, MD, from Harborview Medical Center and the University of Washington, highlighted that successful at-scale AI deployment necessitates trust, transparency, and system-level readiness, beyond mere technical performance. BRIDGE articulates these standards in a clear, actionable manner, providing health systems with the essential structure for responsible, safe, and impactful long-term AI implementation.

The BRIDGE framework is systematically structured around several core areas vital for clinical AI to function effectively in real-world settings. These include a clear distinction between AI models and complete solutions, emphasizing the necessary infrastructure, workflow integration, and user experience. It also defines Minimum Viable Production Environment (MVPE) requirements, detailing technical conditions, validation protocols, regulatory checkpoints, and cost benchmarks crucial before clinical deployment. Furthermore, BRIDGE addresses trust-building mechanisms, promoting transparency, explainability, and defensibility of results across diverse clinical settings and user types. Lastly, it provides scalability guidelines covering interoperability, coordination across multiple models, agentic automation, and long-term performance monitoring across various departments and data types.

These components collectively form a unified structure for evaluating, purchasing, and deploying AI solutions in healthcare. Importantly, BRIDGE is not a vendor specification but rather a community-aligned framework designed to adapt and evolve with advancements in clinical AI, new technologies, and regulatory changes. It is intended to inform Requests for Proposals (RFPs), guide implementation teams, and foster alignment among AI creators, users, implementers, and decision-makers, helping them transition from theoretical 'proof of concept' to tangible real-world impact.

Leonardo Kayat Bittencourt, MD, PhD, from University Hospitals, noted that BRIDGE offers health systems the necessary foundation to scale AI responsibly and the common language to collaborate effectively. The framework is publicly accessible and can be downloaded for free at www.aibridgeframework.com, inviting ongoing community contributions and insights to shape the future of clinical AI.

Aidoc, the developer behind BRIDGE, is a leading provider of clinical AI solutions. Utilizing its proprietary intelligence engine, aiOS™, Aidoc integrates real-time insights directly into clinical workflows, assisting care teams in reducing diagnostic errors and delivering faster, more accurate care. The company's solutions, which support 100,000 patients daily across over 1,500 hospitals, hold the most FDA-cleared clinical AI solutions among dedicated AI companies, underscoring their commitment to clarity, consistency, and confidence in healthcare.