Inclusive Artificial Intelligence for Accessible Medical Imaging Across Resource-Limited Settings

Introduction

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 specialty that has seen some of the most important applications of AI in recent years.

Current Limitations

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 that if the current trend continues, AI will increase the already pronounced inequalities in global health, particularly for resource-limited settings such as rural Africa, where the majority of the African population lives.

Project Overview

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, moving from existing AI methods mostly developed for high-income settings towards new imaging AI algorithms that are fundamentally inclusive. These algorithms will be:

1. Affordable for resource-limited clinical centers.
2. Scalable to under-represented population groups.
3. Accessible to minimally trained clinical workers.

Socio-Ethical Investigation

Furthermore, AIMIX will investigate the socio-ethical principles and requirements that govern inclusive AI. The project will examine how these principles compare, conflict, or complement those of trustworthy AI developed thus far in high-income settings.

Practical Application

These innovations will be demonstrated for affordable and accessible AI-powered obstetric ultrasound screening by minimally trained clinicians such as midwives in rural Africa.

Expected Impact

Ultimately, AIMIX’s scientific breakthroughs will enhance the democratization of imaging AI in resource-limited settings. This will result in an important social impact by empowering local communities, promoting inclusion, and reducing disparities between populations from low- and high-income societies.