Project description
Medical imaging powered by AI for resource-limited settings
AI has significant applications in healthcare. Radiology is a medical specialty that has greatly benefitted from AI applications. However, current AI developments in medical imaging mostly target high-income countries. Should this trend continue, the already pronounced inequalities in global health, particularly in rural Africa, will increase. The ERC-funded AIMIX project will develop a novel scientific framework for inclusive imaging AI in resource-limited settings, scalable to under-represented population groups and accessible to minimally trained clinical workers. The project will advance the current state of the art, from existing AI methods developed for high-resource clinical settings towards new fundamentally inclusive imaging AI algorithms. AIMIX will also investigate the socio-ethical challenges and requirements of inclusive AI tools to promote future implementations in local settings.
Objective
Artificial intelligence (AI) is widely regarded as one of the most promising and disruptive technologies for future healthcare. As AI algorithms such as deep neural networks are suited for the processing of large and complex datasets, radiology is the medical speciality that has seen some of the most important applications of AI in the recent years. However, despite these advances, a major limitation of current AI developments in medical imaging is that they have overwhelmingly, and almost entirely, targeted applications in high-income countries. There is a concern, if the current trend continues, that AI will increase the already pronounced inequalities in global health, in particular for resource-limited settings such as rural Africa, where the majority of the African population lives.
AIMIX will develop the first scientific framework for inclusive imaging AI in resource-limited settings. The project will greatly advance the current state-of-the-art, from existing AI methods mostly developed for high-income settings, towards new imaging AI algorithms that are fundamentally inclusive, i.e. (1) affordable for resource-limited clinical centres, (2) scalable to under-represented population groups, and (3) accessible to minimally trained clinical workers. Furthermore, AIMIX will investigate the socio-ethical principles and requirements that govern inclusive AI, and examine how they compare, conflict or complement those of trustworthy AI developed thus far in high-income settings. These innovations will be demonstrated for affordable and accessible AI-powered obstetric ultrasound screening by minimally trained clinicians such as midwives in rural Africa.
Ultimately, AIMIX’s scientific breakthroughs will enhance the democratisation of imaging AI in resource-limited settings, which will result in an important social impact, by empowering local communities, promoting inclusion, and reducing disparities between populations from low- and high-income societies.
Fields of science
Keywords
Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Funding Scheme
HORIZON-ERC - HORIZON ERC GrantsHost institution
08007 Barcelona
Spain