A total of 38 pioneering artificial intelligent projects from across the UK have been awarded a share of £36 million to test their technology. The projects will help the NHS to transform the quality of care and the speed of diagnoses for conditions such as lung cancer.
Health and Social Care Secretary Matt Hancock announced the winners of the second wave of the NHS AI Lab’s AI in Health and Care Award. The 38 trailblazing projects backed by NHSX and Accelerated Access Collaborative (AAC) include projects from across the region.
Paige prostate cancer detection tool
University of Oxford
Using AI-based diagnostic software to support the interpretation of pathology sample images, in order to more efficiently detect, grade and quantify cancer in prostate biopsies. This helps address a rise in caseload while there are too few qualified pathologists, which has led to resource shortages in the NHS
Ultromics Ltd Oxford, A fully automated and scalable application for quantification and interpretation of stress echocardiograms that autonomously processes “real world” echocardiographic image studies to predict prognostically significant cardiac disease.
Mirada Medical Ltd Oxford,
DLCExpert uses artificial intelligence software to automate the time-consuming and skill-intensive task of outlining (or “contouring”) healthy organs on medical images for radiotherapy planning so that they are not irradiated during treatment.
ICNH Ltd, Windsor, Berkshire
DrDoctor uses AI to get the greatest use from every scheduled appointment within a hospital. It ensures attendance is as high as possible by using past appointment attendance and demographic data to predict those less likely to attend in the future and customising communication with these demographics accordingly.
Brainomix Ltd, Oxford. A set of tools that uses AI methods to interpret acute stroke brain scans, and helps doctors make the right choices about treatment and the need for specialist transfer of patients with confidence. It also provides a platform for doctors to share information between hospitals in real-time avoiding the delays that can occur.
WYSA Ltd, Reading. Real-world testing of an AI app as an early intervention and support tool for mental health, to be used by patients on the waiting list for regular care. The aim is to reduce symptoms of anxiety and depression, and detect people experiencing severe mental health difficulties, so that they can be prioritised for treatment.
Optellum Ltd, Oxford
Optellum’s AI decision support helps doctors make optimal decisions for patients with potentially cancerous lung lesions found in CT scans. The aim is to reduce the time to cancer treatment, increase survival rates, and reduce unnecessary invasive procedures.
Workforce deployment solutions
Navenio Limited, Reading.
Using AI to implement workforce solutions, ensuring that both logistics and clinical support teams are in the right place at the right time within a hospital, to maximise efficiency. Built on Oxford University-originated and infrastructure-free indoor location AI technology that simply uses smartphones to sensitively automate the deployment of teams.
Tim Weil, CEO and Co-Founder at Navenio, said: “The Navenio team is both honoured and delighted to receive the AI in Health and Care Award. The funding will help us accelerate being able to support more teams and patients across the NHS, as we look to build on the positive impact that our technology has provided, particularly during the pandemic. Artificial intelligence is one of many technologies making a real world impact in the healthcare sector, and Navenio is proud to help spearhead digital transformation alongside the other award recipients”
Caristo Diagnostics Ltd, Oxford. Using AI to detect the invisible signatures of inflammation in the heart as shown in regular CT scans. This gives a better prediction of the risk of cardiovascular disease, allowing more efficient targeting of medication and treatment.
Perspectum Ltd, for their First PLUS project, which uses AI to predict Fetal Growth Restriction, a risk factor for stillbirth.