Funding available for artificial intelligence-supported early fracture diagnosis
Organisations can apply for a share of £240,000, including VAT, to develop an innovative AI solution for radiological diagnosis of limb fractures.
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 overall programme will be delivered in 2 phases. A decision to proceed with phase 2 will depend on the outcomes from phase 1. Only successful applicants from phase 1 will be able to apply to take part in phase 2.
NHS Scotland and Opportunity North East (ONE) are investing up to £240,000, including VAT, in innovative data analytics technology. The aim is to improve front-line clinical decision making and patient management in unscheduled care facilities.
The solution will improve clinical workflow and safety by optimising clinical decision making and management pathways. It must use artificial intelligence (AI) or machine learning algorithms to interpret data from upper limb (wrist or hand) and lower limb (ankle or foot) radiographs and linked text-based reports. Accurate determination of the presence or absence of a fracture in these areas has the potential to significantly improve patient care.
Phase 1 research and development contracts will be focused on feasibility studies. Phase 2 contracts will be prototype development and testing.
To lead a project, you can be an organisation of any size, working alone or with others from business, the research base or the third sector as subcontractors.
Phase 1 projects must start by October 2019 and last up to 3 months. Applications must be made by 24th July.
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 of up to 5 projects, for up to 3 months.
To apply, click here.