University Hospitals deploys Aidoc AI platform across 13 hospitals for faster diagnosis of acute conditions

University Hospitals needed a standardized, highly accurate AI platform that could be seamlessly integrated across its network of 13 academic hospitals and dozens of outpatient locations. Having used AI only in small-scale applications, UH sought to expand capabilities to help care teams address pressing medical issues including pulmonary embolism, aortic dissection, vertebral compression fracture, and pneumothorax.

UH deployed Aidoc's aiOS™ platform across 13 hospitals and dozens of outpatient locations, integrating 17 FDA-cleared AI algorithms for triage, quantification, and care coordination. When patients undergo CT scans, Aidoc's AI analyzes the images, identifies both expected and unexpected findings, helps physicians prioritize urgent cases, and facilitates communication between care team members to speed treatment.

The deployment enables faster diagnosis and treatment of acute conditions across the entire UH health network. Care teams gain immediate access to critical patient information, allowing clinicians to access precise, actionable data quickly and improve care coordination. The platform also addresses common AI implementation challenges including EHR compatibility and data management.

• Health system-wide AI standardization requires a platform that handles EHR integration and IT compatibility out of the box, not just algorithmic accuracy.
• Deploying AI for radiology triage at enterprise scale demands governance and continuous monitoring frameworks alongside the clinical tools.
• Expanding from small-scale AI pilots to full health system deployment is achievable when the vendor's platform abstracts away technical complexity.