News

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Recent highlights

Conference room with people seated at tables, a presenter standing near a large screen displaying a presentation titled 'Targets Without Numbers: Making Targeted Validation Scalable,' with logos of CHAI, University of Exeter, and CERSAI.

Launch of the Exeter Regulatory Policy Forum (RPF)

Group of people standing outside of a church or historical building, posing for a photo on a sunny day.

How can clinical prediction models (CPMs) be made more robust and trustworthy?

This was the motivation for an event held at the University of Exeter on July 8th. The workshop, 'Target Without Numbers: Making Targeted Validation Scalable', aimed at developing a holistic view on the validation of clinical models that includes factors beyond strictly statistical considerations. The thirty invited participants brought with them a wide range of expertise across computer science, statistics, epidemiology, clinical practice, social sciences, regulation and policy. 

Event call success

This workshop was held on 6 October 2025 at St Luke’s Chapel, Radcliffe Observatory Quarter, Oxford, was an exceptional and inspiring event. Organised by Catia Nicodemo, Aziz Sheikh, and Cristina Tealdi, it brought together leading academics, researchers, and practitioners to explore innovative ways of applying causal artificial intelligence to contemporary healthcare challenges.

Throughout the day, participants engaged with pioneering ideas — from Bayesian approaches to causal inference and the integration of digital technologies in care, to discussions surrounding the regulation, evaluation, and implementation of AI in healthcare systems. Each presentation offered fresh perspectives on how AI can be responsibly and effectively utilised to improve patient outcomes and inform policy development.

The workshop fostered an atmosphere of collaboration and intellectual curiosity, encouraging meaningful dialogue and paving the way for future research partnerships.

We would also like to express our heartfelt thanks to the CHAI Hub for their generous sponsorship and invaluable support, which made this event possible. Overall, the workshop was a resounding success, providing valuable insights, inspiring new directions for research, and reinforcing our collective commitment to advancing the role of causal AI in healthcare policy and practice.

Reflections from Professor, Catia Nicodemo - event organiser.

A group of six people sitting around a white conference table inside a meeting room, engaged in a discussion. The room has white walls, purple chairs, and wooden doors. One woman is speaking while others listen attentively.

CHAI Community of Practice: Evidence for Regulators

Our first in-person Community of Practice event, held in Manchester on 15 October, was a resounding success! The session brought together a diverse group of about 30 participants—including patients, clinicians, healthcare professionals, regulators, and experts in AI and statistics—to focus on the crucial topic of evidence and guidelines in groups with multiple long-term conditions (multimorbidity) and polypharmacy (people on many medications).

The first half of the session comprised a range of short talks. A highlight was Stella Finlay's moving description of the challenges faced from a patient perspective. The audience was also treated to provocative questions, such as "do we still need causal AI in the age of large language models?" posed by AI researcher Chris Yau. We gained valuable regulatory insight from Patrick Muller, who provided an overview of how NICE (the National Institute for Health and Care Excellence) incorporates real-world evidence and causal AI into their guideline development, and explained how interested researchers can connect with this process.

We concluded with future plans for the group - Sohan Seth explained about opportunities in CHAI and plans to write a position paper and get together again. Overall, it was a fantastic session that generated a rich exchange of interesting perspectives from all participants! We look forward to continuing this vital work.