This paper is in the following e-collection/theme issue:

Pilot studies (non-ehealth) (83) Imaging Informatics (250) Artificial Intelligence (1832) Medical imaging (74) Presbyopia and other Age-related Eye Diseases and Vision Impairments (12) Artificial Intelligence in Diabetes Care and Prevention (44)

Published on in Vol 8 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/59914, first published .
Assessment of Clinical Metadata on the Accuracy of Retinal Fundus Image Labels in Diabetic Retinopathy in Uganda: Case-Crossover Study Using the Multimodal Database of Retinal Images in Africa

Assessment of Clinical Metadata on the Accuracy of Retinal Fundus Image Labels in Diabetic Retinopathy in Uganda: Case-Crossover Study Using the Multimodal Database of Retinal Images in Africa

Assessment of Clinical Metadata on the Accuracy of Retinal Fundus Image Labels in Diabetic Retinopathy in Uganda: Case-Crossover Study Using the Multimodal Database of Retinal Images in Africa

Authors of this article:

Simon Arunga1 Author Orcid Image ;   Katharine Elise Morley2 Author Orcid Image ;   Teddy Kwaga1 Author Orcid Image ;   Michael Gerard Morley3 Author Orcid Image ;   Luis Filipe Nakayama4, 5 Author Orcid Image ;   Rogers Mwavu6 Author Orcid Image ;   Fred Kaggwa7 Author Orcid Image ;   Julius Ssempiira8 Author Orcid Image ;   Leo Anthony Celi5, 9, 10 Author Orcid Image ;   Jessica E Haberer2 Author Orcid Image ;   Celestino Obua11 Author Orcid Image
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