Lab profile
About CERSI-AI
CERSI-AI works with innovators, regulators, patients and the NHS to optimize the regulation of AI and digital healthcare technologies to accelerate innovation that improves people's lives. The center uses scientific methodology to address current and future needs in AI and digital health regulation, aiming to make the UK a global leader where innovators can develop, evaluate and market new products and where patients and health staff can safely benefit from AI-enabled healthcare.
01 · Research focus
Research areas and highlights
Topics and recent work as stated on the lab’s own site.
- Optimising SDEs for AI Health TechnologiesExplores how Secure Data Environments can be optimized to support AI health technology development while balancing innovation, privacy and governance.
- Qualification and Classification of Large Language ModelsClarifies when large language models should qualify as medical devices in healthcare and defines LLM use cases, risk classification and regulatory guidance.
- The AI Readiness ChecklistA practical self-assessment tool helping UK healthcare organizations prepare for safe, effective and equitable AI adoption.
- Hardian Regulatory Intelligence Platform (HaRi)Brings together global medical device regulatory and safety data into one connected system to support faster, safer, and more transparent decision-making.
- Borderline Manual for Software as a Medical Device (SaMD)/ AI as a Medical Device (AIaMD)Provides practical UK guidance on classifying AI health technologies as medical devices, clarifying regulatory status, risk classification and compliance pathways.
- Establishing a public dialogue on Ambient Voice Technologies in the NHSUK public dialogue on NHS AI scribes, capturing patient concerns, trust conditions, and recommendations for transparent, safe, equitable future national implementation.
- Qualifying Large Language Models for Oversight in Patient Safety GovernanceEvaluates how large language models can support NHS patient safety governance and develops qualification frameworks for safe, transparent regulatory use.
- Model stress testing using causal generative AIUses causal generative AI to stress test medical imaging models with realistic synthetic data to identify performance weaknesses.
02 · People
Leadership and researchers
People listed on the lab’s team pages, by role.
03 · Research intelligence
Research Intelligence evidence
Publications, grants and clinical trials linked to the lab’s researchers in Health AI Central’s research data.
Publications & preprints
- Artificial intelligence-supported diabetic retinopathy screening in Tanzania: a randomised controlled trial.The Lancet. Global health · 2026
- Ethical principles and considerations in health AI.Patterns (New York, N.Y.) · 2026
- A mixture of ophthalmic foundation models enables mitigation of altitude-associated domain shift.Science bulletin · 2026
04 · Updates
Updates and lab news
News and events from the lab’s own site.
- AI and Professional Liability in Health and Care — Opportunities for ActionNewsSep 3, 2026 · cersi-ai.org
- Stress Testing Medical AI: Could Generative AI Help Build Safer and Fairer Healthcare Systems?NewsAug 24, 2026 · cersi-ai.org
- Europe needs stronger regulatory science for medical AI and MedTechNewsAug 6, 2026 · cersi-ai.org
- Pushing your device through MHRA Regulation?NewsJul 29, 2026 · cersi-ai.org
- Healthcare Professional Identities in the AI AgeNewsJun 30, 2026 · cersi-ai.org
- The Critical Clarity Health and Care NeedsNewsJun 23, 2026 · cersi-ai.org
- AI Scribes Report Launched at House of LordsNewsJun 22, 2026 · cersi-ai.org
- Clinical Evidence for SaMD and AI Devices: A Practical Guide for ManufacturersNewsJun 4, 2026 · cersi-ai.org
05 · Official presence
Lab sources and channels
The lab’s own pages and accounts.
06 · Related
Related labs and centers
Labs at the same institution and labs working on similar topics.