Artificial Intelligence-Supported Early Fracture Diagnosis

Key Features

Organisations can apply for a share of £240,000, including VAT, to develop an innovative AI solution for radiological diagnosis of fractures of upper and/or lower limbs.

Programme:     Innovate UK - SBRI

Award:     Share of up to £240,000

Opens: 20th May 2019

Closes: 31st Jul 2019

! This scheme is now closed


This is a Small Business Research Initiative (SBRI) competition funded by Opportunity North East and NHS Scotland. Successful applicants will receive 100% funding and have access to advice from NHS Grampian, NHS Greater Glasgow and Clyde (NHSGGC), the University of Aberdeen, the Canon Medical Research Europe and the funders.


The challenge is to develop an AI or machine-based learning programme that can help healthcare organisations accurately identify whether a patient has a fracture. This is initially a classification problem (by assigning a value of yes, no or maybe).

AI or machine learning could be included in clinical workflows to interpret peripheral limb radiographs for the presence of fractures, which in most cases are not reported for several days. This would help:

  • improve diagnostic accuracy and treatment
  • improve patient pathways and outcomes
  • reduce the growing deficit between radiology reporting workloads and staffing levels

This competition draws on Scotland’s expertise in:

  • clinical and academic digital radiology
  • advanced data storage
  • data governance and access
  • interoperable healthcare databases

The competition is looking for proposals that:

  • improve peripheral limb fracture detection by non-radiology experts in out of hours environments within NHS Grampian
  • transform peripheral limb injury clinical pathways to improve patient outcomes and increase productivity by at least 20%
  • use the relevant NHS, academic and commercial expertise, data and infrastructure offered by Grampian
  • have clinical and commercial potential locally, nationally and globally

In phase 1, you must:

  • demonstrate the technical feasibility of your proposed innovation
  • establish ongoing collaboration between technical and clinical members of the project team
  • formalise any required ethical approvals, data sharing agreements and contracts
  • begin working with clinical and imaging data


To lead a project, you can:

  • be an organisation of any size
  • work alone or with others from business, the research base or the third sector as subcontractors

Applications are welcomes that bring together a consortium of sector specialists.

Innovate UK are looking for industrial innovators. You must confidently collaborate and use multiple data sources to develop clinically relevant and commercially practicable solutions. There is potential to commercialise outputs directly through NHS Scotland and globally through the sales and marketing channels of Canon Medical.

Funding Costs

NHS Scotland and Opportunity North East have allocated up to £240,000, including VAT, to fund projects in this competition. There are 2 phases. Up to £100,000, including VAT, is allocated for phase 1 and up to £140,000, including VAT, for phase 2.

Phase 1 projects must start by October 2019 and last up to 3 months.

It is anticipated that the feasibility study R&D contracts will be in the region of up to £20,000, including VAT. This is for each project for up to 3 months. It is expected that phase 1 will fund up to 5 projects.

Applications must have at least 50% of the contract value attributed directly and exclusively for R&D services. R&D can cover solution exploration and design. It can also include prototyping and field-testing the product or service. R&D does not include:

  • commercial development activities such as quantity production
  • supply to establish commercial viability or to recover R&D costs
  • integration, customisation or incremental adaptations and improvements to existing products or processes

The total funding available for the competition can change. The funders have the right to:

  • adjust the provisional funding allocations between the phases
  • apply a ‘portfolio’ approach