Leiden University Medical Centre

Leiden University Medical Centre (LUMC), a tier 3 academic hospital in the Netherlands, faced increasing radiology workloads and growing demand for more efficient resource allocation. Retrospective validation revealed that 40–50% of chest X-rays contained no pathological findings, representing a large pool of routine studies consuming radiologist time that could otherwise be redirected to complex cases.

LUMC deployed Oxipit's AI solutions (ChestLink and/or ChestEye) to automatically identify and clear normal chest X-ray studies, streamlining triage and enabling radiologists to focus on studies that actually require their expertise.

• Even top-tier academic centres can have 40–50% of chest X-rays come back normal, making autonomous AI a high-leverage intervention.
• Retrospective validation is a practical first step before committing to a live autonomous workflow.
• Workflow optimisation and resource reallocation—not just diagnostic accuracy—are primary drivers of AI adoption in academic radiology.