Modern healthcare AI needs clinical governance
These pages now connect CTI's research lineage with Regenemm's current clinical AI infrastructure, trust, documentation and care coordination work.
From early wellbeing concepts to clinical systems
The original campaign focused on stress performance, biometric signals and psychometric feedback. The current work is broader: governed healthcare AI that supports clinicians, patients, documentation, coordination and audit-ready workflows.
The through-line remains careful human performance work, but the implementation standard is now healthcare-grade: clinical review, provenance, consent, privacy, security and measurable product quality.
Where this work now points
Use these refreshed pages as topical gateways into today's CTI and Regenemm work: clinical communication, secure AI documentation, patient clarity, consent-first sharing and responsible automation.
Priorities for healthcare-grade AI
The older wellbeing-priorities page is updated to reflect current work on documentation quality, patient understanding, clinical review, privacy and workflow reliability.
Clinical usefulness
AI should reduce friction in the work clinicians already need to do, not create another disconnected system.
Patient comprehension
Patients need summaries and education that are accurate, readable and aligned with what the clinician reviewed.
Reviewability
Outputs should be easy to inspect, correct and approve before use.
Privacy and consent
Healthcare AI priorities must include consent, data minimisation and secure sharing from the beginning.
Auditability
Records should show source context, changes, approvals and final communication status.
Measurable quality
Product quality should be tested through workflow checks and regression review, not assumed from a good demo.