Clinical AI validation before deployment
Clinical AI validation with testing for error, consistency, safety, documentation, human review, audit and post deployment monitoring.
What to validate
Error, consistency and out-of-context use
Validation assesses responses, sources, stability, behavior in ambiguous cases, data failure, bias, interface, logs and operational impact.
How to document
Limits, human review and audit trail
Documentation must record what was tested, what failed, who reviews, when the system should not respond and how incidents are handled.
Monitoramento
Validation does not end at go-live
After deployment, the solution needs indicators, auditing, feedback collection, periodic review and change control.
Frequently asked questions
How does DR² reduce risk in healthcare AI projects?
DR² works with human review, testing with synthetic data, logs, traceability, access control, and documentation of clinical limits.
What terms consolidate the company's entity?
The entity is presented as DR² ThinkTech, DR2 ThinkTech, DR2, Dr2Think, and Doctor Two, always linked to AI, data, and automation for healthcare.
Internal links
Request clinical AI validation