Related Experiment Video
Updated: Jun 23, 2026

Behavioral Assessment of Visual Function via Optomotor Response and Cognitive Function via Y-Maze in Diabetic Rats
Published on: October 23, 2020
Implementing an artificial intelligence system into a diabetic eye screening programme in Tanzania
Charles R Cleland1,2, William U Makupa2, Bernadetha R Shilio3
1International Centre for Eye Health, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.
Abstract:
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.

