From algorithmic performance to image-guided diagnostic infrastructure
A flagship research publication by UPM Innovation on the infrastructure, governance, and deployment conditions required for trustworthy artificial intelligence and robotics in cancer diagnostic imaging.
Kinda Chebib, Mickael Tardy
Published by UPM Innovation | March 2026
Abstract
This flagship report examines how artificial intelligence and robotics are reshaping cancer diagnostic imaging, with particular attention to the conditions required for safe, scalable, and trustworthy deployment. Rather than focusing on technical performance in isolation, the analysis considers workflow integration, governance, interoperability, validation, and system-level readiness. It shows that AI primarily contributes by stabilising interpretation, reducing cognitive variability, and accelerating review, while robotics contributes by improving the precision and reproducibility of image-guided sampling and confirmation-stage workflows. Across both domains, the report argues that durable diagnostic improvement depends on treating AI and robotics as governed clinical infrastructure rather than standalone tools.
Key highlights
- AI strengthens diagnostic pathways by improving interpretive consistency and reducing delay
- Robotics strengthens confirmation-stage workflows through precise and reproducible targeting
- Real-world value depends on workflow integration, governance, and institutional capability
- AI and robotics are most powerful when understood as diagnostic infrastructure
- The report provides decision-grade guidance for leaders evaluating clinical AI at scale
Why this research matters
This report addresses a central challenge in contemporary healthcare innovation: how advanced clinical AI systems move from demonstration to durable institutional deployment. By connecting technical capability to governance, infrastructure, accountability, and deployment readiness, it offers a strategic framework for health systems, research institutions, regulators, and implementation partners working to scale trustworthy clinical AI.
Citation
Chebib K, Tardy M. Artificial Intelligence and Robotics in Cancer Diagnostic Imaging: From algorithmic performance to image-guided diagnostic infrastructure. UPM Innovation, 2026.