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

Pilot studies (non-ehealth) (83) Imaging Informatics (250) Artificial Intelligence (1836) 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
Article Authors Cited by (1) Tweetations Metrics

Conference Proceedings

  1. Rajput S, Gupta S. 2025 3rd International Conference on Data Science and Information System (ICDSIS). Multimodal Framework for Early Detection and Progression Prediction of Diabetic Retinopathy View