Mayo Clinic has roughly 150 AI models across its health system, covering everything from AI scribes and early cancer detection to ECG analysis, pathology and emergency-department triage.
Some are already used in clinical practice, while others are still being validated or developed.
They all require computing power, data and robust governance.
Mayo's approach to AI is not simply to develop a model and immediately put it into clinical use: The organization has established an AI governance and lifecycle-management process under which clinical AI applications undergo review before Mayo staff can use them.
The assessment can include model performance, patient safety, workflow integration, privacy, security, and lifecycle management.
Depending on the application, validation may involve retrospective studies, prospective clinical research or other forms of evaluation.
Once deployed, applications are subject to ongoing performance and lifecycle monitoring.
This is particularly important because an AI model that performs well during development can behave differently when exposed to new patient populations, workflows or data.
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