Thirty-eight new pioneering artificial intelligence (AI) projects announced to help revolutionise care and accelerate diagnosis.
Thousands of patients and NHS staff will benefit from dozens of new pioneering projects awarded a share of £36 million to test state-of-the-art AI technology. The projects will help the NHS to transform the quality of care and the speed of diagnoses for conditions such as lung cancer.
At CogX Festival today (16 June), the 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:
- an AI-guided tool to help doctors and nurses to diagnose heart attacks more accurately
- an algorithm to fast-track the detection of lung cancer
- an AI-powered mental health app to help tackle symptoms of anxiety and depression while also identifying people experiencing severe mental health difficulties
- tech to help spot undiagnosed spinal fractures
Already over 17,000 stroke patients and over 25,000 patients with diabetes or high blood pressure have benefited from the first round of the AI in Health and Care Award since September, where £50 million was given to 42 AI technologies.
Health and Social Care Secretary, Matt Hancock said:
Sir Simon Stevens, chief executive of NHS England, said:
The AI in Health and Care Award aims to accelerate the testing and evaluation of AI in the NHS so patients can benefit from faster and more personalised diagnosis and greater efficiency in screening services.
For example, use of Paige Prostate will be able to give more information about prostate cancer, including detecting a tumour, its size and how severe it is, enabling clinicians to make treatment more specific and more targeted. As well as this, Mia by Kheiron Medical, a winner from the first round of the AI Awards, aims to replace the need for 2 radiologists to review breast cancer scans by instead using one radiologist and the AI, making the process faster and more efficient.
The 38 projects which are being supported by the second wave of the AI Awards include:
- an algorithm from BeholdAI that can identify suspected lung cancer in chest X-rays to increase the numbers of cancers diagnosed and reduce the time patients wait for scans
- The Paige Prostate cancer detection tool to help pathologists identify cancers and their spread in digital images to improve diagnostic accuracy and help tackle rising caseloads
- Zebra Medical’s Bone Health Solutions tool to analyse existing CT scans to look for previously undiagnosed spinal fractures that could be a sign of osteoporosis to find more patients living with this undiagnosed disease, ensuring they receive appropriate advice or medication
- Mental health app Wysa – an AI-powered chatbot and series of self-care exercises which will provide mental health support, helping people manage their mental health. Patients will be given access to the app during the referral process for mental health services, to explore whether the app can ease symptoms of anxiety and depression before patients receive assessment and treatment
Matthew Gould, chief executive of NHSX, said:
Matt Whitty, Chief Executive, Accelerated Access Collaborative and Innovation, Research and Life Sciences Director, NHS England and NHS Improvement, said:
The AI award package also includes funding to support the research, development and testing of early phase, promising ideas which could be used in the NHS in future:
- diagnosing heart attacks – an AI-guided tool that could diagnose heart attacks more accurately and quickly through better interpretation of blood analysis
- monitoring cystic fibrosis – using AI with home monitoring equipment to predict sudden dips in the health of cystic fibrosis patients, aiming to prevent them occurring
- monitoring brain tumours – developing AI to measure the volume of brain tumours from scans to assess which are at risk of growth to ensure those patients are monitored more frequently
- improving kidney transplant outcomes – using data from 20 years of previous kidney transplants to improve the decision-making process for a patient to receive less-than-perfectly-matched donor kidneys or wait for the next available one
- detecting bowel cancer – using AI to analyse video recordings of the gastrointestinal tract, taken from a swallowable camera, to target bowel cancer and other gastrointestinal diseases