Tanzania has the highest age-adjusted prevalence of diabetes in sub-Saharan Africa. Diabetic retinopathy, a common complication, is a significant cause of vision loss; but with effective screening and treatment this often can be prevented. However, with very few specialist eye care staff in Tanzania this is a major challenge. Artificial intelligence (AI) systems, which automate clinical decision making and therefore task-shift away from specialist staff, could contribute to improved diabetic retinopathy screening services in low-resource settings. This article describes our experiences of selecting, procuring and implementing an AI system into a regional diabetic eye screening programme in northern Tanzania.
Keywords: artificial intelligence; diabetic retinopathy; implementation; screening.
© The Author(s) 2024. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene.