Clinical AI firm Aidoc, in conjunction with NVIDIA, has released a new framework to guide healthcare organizations' clinical AI deployment.
Named BRIDGE -- an acronym for Blueprint for Resilient Integration and Deployment of Guided Excellence -- the framework gives guidance for assessing AI-based applications by outlining the technical, regulatory, operational, and trust-building criteria that AI should meet before deployment, Aidoc said in a statement.
BRIDGE was designed with input from 17 organizations, including the University of Washington, University Hospitals, and Ochsner Health, according to Aidoc.
The BRIDGE framework is structured around four core areas that determine whether a clinical AI application can function safely and effectively in real-world settings: a clear distinction between models and full solutions, minimum viable production environment requirements (i.e., technical conditions, validation protocols, regulatory checkpoints, and cost benchmarks), trust-building mechanisms, and scalability guidelines.
As a framework, BRIDGE is intended to be dynamic and evolve over time, Aidoc said.
BRIDGE is publicly available here.















![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&fit=crop&h=112&q=70&w=112)



