The government has announced that £13 million is to be made available from the UK Research and Innovation’s Technology Missions Fund to support 22 health research projects which focus on the use of artificial intelligence to “assist and refine” diagnostics and procedures.
The projects are to use AI in a variety of ways:
- advancing machine learning to support real-world early detection and personalised disease outcome of inflammatory arthritis (University of Reading)
- real-time analysis of healthcare infodemics to identify misinformation and create clinical guidance (Imperial College London)
- developing a self-training platform for laparoscopic surgery (Heriot-Watt University)
- developing a predictive tool for the impact of pollution on health (Imperial College London)
- diagnosis and treatment of age-related macular degeneration, with focus on protecting privacy (Imperial College London)
- developing risk prediction models for multiple long-term conditions (University of Oxford)
- determining the clinical impact of newly discovered variations in the genome (University of Southampton)
- scaling and validating a foundation model for ophthalmology (University College London)
- developing novel cancer diagnosis techniques using soft tissue tumours as a use case (University College London)
- analysing breathing and speech to identify patients at risk of developing severe respiratory tract infections (University of Cambridge)
- optimising natural language processing for real-time structured clinical data capture in electronic health records (University College London)
- determining how location and environment factors affect behaviours and targeting public health interventions (University of Cambridge)
- developing a decision support framework to improve pituitary surgical outcomes (University College London)
- combining Internet of Things sensors and AI to detect pollens and spores and forecast their impact on human health (University of Birmingham)
- identifying new biomarkers and developing therapeutics for chronic pain (University of Sheffield)
- genomic profiling to reveal drug resistance mutations and transmission patterns in infectious diseases (London School of Hygiene and Tropic Medicine)
- developing new AI for neuroimaging by leveraging universal fractal geometry (Newcastle University)
- developing a digital twin for enhancing clinical care in respiratory emergency conditions (University of Leicester)
- handling missing data in electronic health records to support prevention of chronic diseases (University of Cambridge)
- developing new guidance and methods for “reliable and fair” AI prediction models for use in healthcare (University of Birmingham)
- developing guidance and methods for mammogram analysis, focusing on co-creation with radiologists (University of Surrey)
- designing new therapies for rare inherited diseases (University of Edinburgh)
In addition, the government has announced that the “first major international summit of its kind” on the safe use of AI is to be held in the UK later this year. Two experts have been selected to lead preparations and support the summit in developing a shared approach to mitigating AI risks: Matt Clifford, CEO of Entrepreneur First and chair of the Advanced Research and Invention Agency and Jonathan Black, Heywood fellow at the University of Oxford’s Blavatnik School of Government and former deputy national security advisor.
In June, the DHSC announced £21 million in funding to “roll out artificial intelligence across the NHS”, hoping to “accelerate the deployment of the most promising AI tools across hospitals to treat people more quickly this winter”.
Developments for the use of AI in UK healthcare over the last year have included a study using AI to create microscopic particles capable of transporting medicines to target and treat diseased cells, as well as research into the use of AI for diagnosis and screening in conditions including breast cancer and dementia.
