Pilots run clean, then stall on live studies. What infrastructure, governance, and PACS integration health systems fixed before scaling, with cited evidence.
Why radiology AI adoption stalls - and what health systems that scaled it did differently By 2055, US imaging demand will rise 16.9%–26.9% above 2023 levels, while the radiologist workforce...
The AI-Ready Hospital: Architecture, Culture, Workflows, and Staffing for the Next Decade An AI-ready hospital is a health system whose data infrastructure, governance, clinical workflows, and staffing are built to...
Large language models (LLMs) have captured the spotlight with their ability to generate fluent, contextual responses across a wide range of medical use cases. But beneath the hype, a quieter...
When Ohio State University built their Medical LLM infrastructure to process over 200 million clinical notes, the technical challenges extended far beyond preventing hallucinations. Their system required unified data ingestion...
Why annotated datasets lose value when schemas change»: «A health system invests years building diagnosis extraction data, de-identification masksReusing clinical annotations across projects means importing existing labeled datasets into a...
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