Implementing an artificial intelligence system into a diabetic eye screening programme in Tanzania

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.

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Publication Details

Journal
Transactions of the Royal Society of Tropical Medicine and Hygiene
Published
2024-12-16
DOI
https://doi.org/10.1093/trstmh/trae132
Primary Topic
Retinal Imaging and Analysis
Type
article
Field-Weighted Citation Impact
0.00

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article

Implementing an artificial intelligence system into a diabetic eye screening programme in Tanzania

Justus Rwiza, David Macleod, Charles R Cleland, Covadonga Bascarán et al.
Transactions of the Royal Society of Tropical Medicine and Hygiene
Retinal Imaging and Analysis
article

Implementing an artificial intelligence system into a diabetic eye screening programme in Tanzania

Justus Rwiza, David Macleod, Charles R Cleland, Covadonga Bascarán, William Makupa, Matthew J. Burton, Bernadetha Shilio
article en

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.

Transactions of the Royal Society of Tropical Medicine and HygieneVol. 119(6)
London School of Hygiene & Tropical Medicine (GB), Ministry of Health, Community Development, Gender, Elderly and Children (TZ), Kilimanjaro Christian Medical Centre (TZ)
Alexander and Margaret Stewart Trust, Wellcome Trust, British Council for Prevention of Blindness, Sir Halley Stewart Trust
Openalex Percentile: Top 60%
Retinal Imaging and Analysis
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