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.
Authors
- Justus Rwiza
- David Macleod (ORCID: https://orcid.org/0000-0002-2371-5709)
- Charles R Cleland (ORCID: https://orcid.org/0000-0002-2761-8092)
- Covadonga Bascarán (ORCID: https://orcid.org/0000-0002-5662-3325)
- William Makupa
- Matthew J. Burton (ORCID: https://orcid.org/0000-0003-1872-9169)
- Bernadetha Shilio
Institutions
- London School of Hygiene & Tropical Medicine (GB)
- Ministry of Health, Community Development, Gender, Elderly and Children (TZ)
- Kilimanjaro Christian Medical Centre (TZ)
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
Funders
- Alexander and Margaret Stewart Trust
- Wellcome Trust
- British Council for Prevention of Blindness
- Sir Halley Stewart Trust