Digital Futures, in partnership with The University of Manchester, The Christabel Pankhurst Institute, ECH Alliance and Health Innovation Manchester, hosted AI in Healthcare: Transforming the Future with Large Language Models #2, a follow-up due to the huge success of the part one!
The event was held at Manchester-based Core Technology Facility on 6th October 2025. It hosted four incredible healthcare industry- and AI-based speakers, and gave attendees a second opportunity to discuss the challenges of AI in health and care.
Sabine Van Der Veer, Senior Lecturer in Health Informatics at The University of Manchester, was present as the Chair of the event. Sabine provided a fantastic in-depth overview of Digital Futures and its' five theme areas. She also announced her exciting new role as Digital Health Theme Lead!
Dr Saif Ahmed, a GP and Clinical Digital Lead at Health Innovation Manchester, provided a short introduction on the place-based innovation organisation. Saif explained that HInM are academic health and science network, aiming to boost the economy for Manchester through industry partnerships. HInM place focus on digital and data as part of its vision, with digital projects around Digital Workforce, Digital Inclusion, Digital First Primary Care, and NHS at Home at Scale in the works for the organisation.
Dr Benjamin Brown, Co-Founder and Chief Medical Officer at Patchs Health, presented first on the day, with his focus being AI Triage in Primary Care. Ben spoke about the process of using an AI model. After a user provides their information, Patchs collects the inputs (demographics and query), runs these through a Large Language Model, classifies the LLM output, then follows by running final checks with a safety guardrail. The AI then can action questionnaires, further advice, links to self-help books, or signpost to other services. You can watch Ben's presentation in full above.
Dr Tim Murdoch, Chief Product Officer at Proxximos, presented next, with his speech on Digitising Infection Control - How Far Should We Go?. Tim explained that Proxximos focuses on hospital acquired infections and how to reduce them. He noted that one in five beds in the UK and across Europe (and the US) is occupied by someone that got an infection whilst in hospital. Proxximos conducted a study which took place in Manchester at Wythenshawe Hospital, in the Respiratory ICU. Patients and staff wore a tracking badge, which identified if someone had transmitted an infection to someone else in the pilot area. Their data can seek out who is high risk, and stop further people becoming infected. You can watch Tim presentation above.
Dr Chris Nortcliff, NHS GP and CCIO & Digital Lead at Greater Manchester Primary Care Provider Board, was our third speaker to present, discussing LLMs in General Practice – Finding the Sweet Spot. Chris emphasised that AI is too valuable to not be used, but also asked the questions "What are the right options?", "What are the right environments to use it in?", and "When should we be using it?". He also discussed improving the quality of what humans do with AI refinement. You can catch up on Chris' presentation in full above.
Dr Jingyuan Sun, Lecturer and Assistant Professor in Natural Language Processing at The University of Manchester, was our final presentation of the day, delivering a talk on The Convergent Frontier: How LLMs, Neuroscience, and Mental Health Research are Uniting?. Jingyuan asked the question "Do we have a certain kind of correlation between the Large Language Model and the activations from our human brain?", explained neuro-AI alignment with brain encoding (neural encoding) and brain decoding, and discussed how we can use LLM's to reconstruct from brain activations to the sentences and stories that humans hear. If you missed Jingyuan's presentation, you can catch-up above.
After a networking lunch, a breakout session was then hosted by Sabine, where she asked the large group questions about the challenges of developing and deploying AI in the NHS and healthcare.
Key Takeaways from the Breakout Session (and speaker Q&As)
The audience spoke with Sabine to discuss what their take on the key challenges of developing and deploying AI in the NHS and healthcare. Various topics were highlighted, including governance, ethics and compliance, AI deployment, safety standards, the reliance and trustworthiness of AI, and the transition and implementation of AI into practice. Read below to find out more.
Three major themes discussed amongst the group
Governance, ethics and compliance:
- There is an evolving regulatory landscape for medical devices.
- What the ethical considerations will be, regarding collecting data as an input for an AI-based intervention.
- A large collection of data may be a hinderance rather than a positive.
- Collecting data may be a huge burden on the individuals involves, especially staff and patients in hospitals.
- Data collection is intrusive, in particular when passively collecting data (such as via wearables, for example sensors and monitors).
- Who will be looking at the data and advice that AI will be providing?
- Communities of practice must be established to facilitate learning across areas of the NHS and healthcare systems, as well as across AI innovations.
Safety standards, and the reliance and trustworthiness of AI:
- The provider awareness of clinical safety standards.
- There is a perceived trustworthiness of AI-generated output and advice.
- There is a need and demand for AI-generated output and advice.
- There is also an impact of responding to AI-driven clinical advice, which may be positive or negative.
- What will be the impact of AI-driven clinical advice on clinical pathways and clinical workload?
Costs, and the transition and implementation of AI into practice:
- The need for funding to enable the development of AI interventions.
- Funds also required for evaluating and implementing AI in practice.
- The role of robust evidence in the successful deployment of AI.
- The differences between stakeholder groups regarding the need of rigorous evaluations to fulfil their role within the ecosystem
- What stakeholder groups regard as the main outcomes of interest.
- When implementing AI in practice, what will be the impact on clinical pathways and clinical workload when adopting AI-driven clinical advice?
- How will promising AI innovations expedite and smoothen the translation into clinical practice?
We want to thank all the speakers, attendees, partners, and staff who made this event possible. Keep posted on our Digital Futures Eventbrite to never miss a future GM Connected Health Ecosystem event!
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