Clinical Deployment

doctor review 3d scan of a patients heart

Clinical Deployment

The clinical deployment program links closely with Radiology and Biomedical Imaging PACS operations, and together provide UCSF Health unique quantitative image analytics and metrics to impact patient outcomes.

About this Resource

The clinical deployment program develops strategic, rapid ways of translating the novel developments of the center to the clinical arena. It also is responsible for the deployment of novel models and technologies that may already be FDA approved to the clinical Radiology and Biomedical Imaging workflow, as well as exploring new and emerging opportunities for the translation of AI to clinical imaging.

ci2 logo center of a collage of medical imagery
Doctors discussing imagery on computer screen

Who Can Use This Resource

UCSF scientists and doctors can access the resources of the clinical deployment program.

AI Algorithm Clinical Deployment Evaluation Framework

Framework Description

This is a general framework for evaluation of AI algorithms for clinical deployment. Not all points in this framework will be relevant to every algorithm; each algorithm is likely to have certain unique considerations. This framework tries to give form to the evaluation for approval by covering the most common aspects that should be evaluated, discussed and considered


  • Ready for Clinical Deployment = potentially ready to put into place where they will be used in regular clinical workflow
  • Algorithms that are in clinical validation mode = initial development of algorithm is complete but do some additional validation in a clinical development and not ready to use for clinical decision making

Analysis – Benefits

  • Breadth – how many cases/patients effected?
  • Depth – extent of effect on each case both on patients and radiologists

Risk & Costs - Erroneous Results

  • Detectability
  • Correctability
  • Impact on patients

Risk & Costs - Risk Spectrum

  • Low – prioritization/triage/alerting with little to no impact on patient
  • Moderate – decision/diagnosis support, workflow requires radiology evaluation
  • High – decision/diagnosis support that doesn’t require radiology evaluation
  • Highest – algorithms that produce clinical outputs that where there is no ability for radiologist to crosscheck; zero detectability and correctability of errors

Monitoring & QA

  • Follow-up evaluation of algorithm performance
  • Degree of monitoring correlates to Risk Spectrum

Clinical Deployment Contact Us