Round 1 AI in Health and Care Awards

The winners of the first competition were announced by Secretary of State for Health Matt Hancock on 8 September 2020. Read more details in the media release.


Aidence: An AI platform to optimise oncology pathways, which can be integrated into existing software systems. Veye Chest, the first clinical application, is unique in its ability to currently automate early lung cancer detection, and soon also support treatment response assessment.

e-Stroke Suite

Brainomix Ltd: 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.

RITA: Referral Intelligence and Triage Automation

Deloitte: An AI solution to automate the triage of GP referrals – assessing the urgency and next step for the referral and sending through directly to the next step in the process. In addition the solution includes a virtual assistant that supports clinicians in writing letters back to GPs, significantly speeding up this process.

Smartphone albuminuria self-testing (UK) Ltd: Using a home test kit and mobile app,’s solution empowers patients to self-test at home with clinical grade results. Fully integrated to the Electronic Medical Record (EMR), real-time results are available for clinician review and follow-up. Shifting testing to the home increases uptake, improves quality, reduces workload in primary care, and creates savings.


ICNH Ltd: 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.

Zio Service

iRhythm Technologies Ltd: A complete and clinically proven ambulatory ECG monitoring service, utilising powerful AI-led processing and analysis to support clinical workflows and improve the diagnostic yield and timeliness of cardiac monitoring.

Mia Mammography Intelligent Assessment

Kheiron Medical Technologies: Deep learning software that has been developed to solve critical challenges in the NHS Breast Screening Programme (NHSBSP), including reducing missed cancers, tackling the escalating shortage of radiologists and improving delays that put women’s lives at risk.


Mirada Medical Ltd: 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.

Automated diabetic retinal image analysis software

Optos PLC: OptosAI uses a machine learning algorithm to analyse images of the back of the eye for the presence/severity of any diabetic retinopathy, and then advises if referral to an eye care specialist is needed (based on the local clinical pathway).

EchoGo Pro

Ultromics Ltd: 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.

Artificial Intelligence (AI) in Health and Care Awards: bids invited to evaluate round 1 winners

Bids are being invited by the Accelerated Access Collaborative (AAC) from specialist independent teams to evaluate the winning technologies from round 1 of the AI in Health and Care Award.

The AI in Health and Care Award forms part of the NHS AI Lab and is managed by the AAC in partnership with NHSX and the National Institute for Health Research (NIHR).

The evaluations will assess whether these technologies should be recommended for wider adoption across the NHS and will look at their safety, effectiveness, and impact. Evaluations will be conducted with a real-world perspective and follow NICE appraisal processes.

This call for evaluation teams is split into two stages:

Stage 1: A shortlisting competition where bidders can indicate which of the technology winners from round one they are bidding to evaluate. Bidders should apply using the Bravo platform using the relevant link below.

  • Route A: Where you have no prior relationship working with the technologies you wish to express an interest in. Submission is via Bravo portal, using the code ITT_869, by 9 October 2020 at 12pm.
  • Route B (fast track): Where you have a prior relationship, in an evaluator capacity, working with the technologies you wish to express an interest in. Submission is via Bravo portal, using the code  ITT_872, by 5 October 2020 at 10am.

Stage 2: Following a shortlisting process successful bidders will be invited to a further competition where they will develop an evaluation scoping plan for the technology/technologies they have expressed an interest in from 16 October 2020, with a deadline expected to be 6 November 2020.

The Bravo platform provides further information for bidders. All who register their interest early via the platform will be invited to join a webinar on 30 September 2020 from 1.30pm to 2.30pm, where they will have the opportunity to ask any questions about the awards and the bidding process. Questions and answers will be shared on the Bravo platform for those who cannot attend the webinar.