The winners of the first round of The Artificial Intelligence (AI) in Health and Care Awards have been announced.
The award is making £140 million available over three years to accelerate the testing and evaluation of technologies most likely to meet the aims set out in the NHS Long Term Plan.
Four levels of award are available in each round to support AI solutions – from initial feasibility to evaluation within NHS and social care settings.
It is a competitive process run by the Accelerated Access Collaborative in partnership with NHSX and the National Institute for Health Research.
Each round will support different categories of technology to address clinical and patient need.
The winners of the first award were announced earlier this month with three PIF member projects receiving funding and support.
The PIF members who won awards were:
- Barts Health NHS Trust, Autonomous cardiac MR acquisition. Using AI to fully automate cardiac MRI scans to add precision, help to better predict clinical outcomes, speed up scanning, reduce waiting times and save money. (Phase 1)
- University College London Hospitals NHS Foundation Trust, Natural language processing for real-time data capture in electronic health records to improve clinical care and operational efficiency. Developing a natural language processing system to support the conversion of clinician’s text in electronic health care records into a structured format that can be processed by computers to help support clinical decision making, planning and research. (Phase 2)
- Guy’s and St Thomas’ NHS Foundation Trust, Evaluation of the DEONTICS AI platform for personalised, evidence-based treatment planning in multidisciplinary cancer care. Evaluating how the platform works to triage less complex patients straight to the treating clinicians, whilst also supporting decisions on care for prostate cancer patients with more complex needs. (Phase 3)
A second competition will be launched in November 2020.
Further information and calls for applications to future rounds can be found on the AAC website by clicking on the link below.