Cognis Evidence

Evidence

Peer-reviewed science, multi-centre validation, and a clear pathway toward responsible clinical translation.

Scientific Foundation

Validated AI, Built on Rigorous Evidence

Medical researchers analyzing AI-driven imaging results on a high-resolution screen in a modern hospital radiology department

Our evidence base is anchored in peer-reviewed studies published in leading medical journals. We focus on non-contrast CT imaging, where AI can unlock clinically valuable insights from routine scans. The research behind our approach is designed to meet the standards of clinical institutions, combining algorithmic innovation with real-world patient data.

Beyond initial publication, we believe in continuous validation. Our studies are structured around multi-centre datasets, independent reader studies, and consecutive patient cohorts to ensure that our AI performs reliably across different populations and clinical settings.

Peer-reviewed publications

Multi-centre external validation

Real-world cohort testing

Validation Depth

Key Evidence Metrics

3

Nature Medicine Publications

Including PANDA, GRAPE, and iAorta studies focused on non-contrast CT.

5+

Multi-Centre Cohorts

Validation across diverse hospitals and imaging protocols to ensure generalisability.

10k+

Consecutive CT Scans

Real-world patient data analysed in consecutive cohort studies, reflecting routine clinical practice.

Evidence to Translation

Published evidence is the starting point. We actively work with clinical partners to validate AI tools in their specific environments, ensuring that our technology meets local needs and governance standards before deployment.