The Challenge of Diabetic Retinopathy Standardization in an Ophthalmological Dataset-Reference-Cited by-同舟云学术

The Challenge of Diabetic Retinopathy Standardization in an Ophthalmological Dataset

Published:2021-07-14 Issue:6 Volume:15 Page:1410-1411
ISSN:1932-2968
Container-title:Journal of Diabetes Science and Technology
language:en
Short-container-title:J Diabetes Sci Technol

Author:

Nakayama Luis F¹^ORCID,Gonçalves Mariana B¹²³^ORCID,Ferraz Daniel A¹²³,Santos Helen N V¹,Malerbi Fernando K¹^ORCID,Morales Paulo H¹²,Maia Mauricio¹,Regatier Caio V S¹,Belfort Rubens¹²

Affiliation:

1. Department of Ophthalmology, Universidade Federal de São Paulo - EPM - São Paulo (SP), Brazil

2. Instituto Paulista de Estudos e Pesquisas em Oftalmologia, IPEPO, Vision Institute, São Paulo (SP), Brazil

3. NIHR Biomedical Research Centre for Ophthalmology, Moorfields Eye Hospital, NHS Foundation Trust and UCL Institute of Ophthalmology, London, UK

Funder

Lemann Foundation, Instituto da Visão -IPEPO

CAPES Foundation, Ministry of Education of Brazil

Publisher

SAGE Publications

Subject

Biomedical Engineering,Bioengineering,Endocrinology, Diabetes and Metabolism,Internal Medicine

Link

http://journals.sagepub.com/doi/pdf/10.1177/19322968211029943

Reference6 articles.

1. Accelerating ophthalmic artificial intelligence research: the role of an open access data repository

2. Artificial intelligence and deep learning in ophthalmology

3. Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices

4. Diabetic Retinopathy

5. A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis

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1. Advancing healthcare with artificial intelligence: diagnostic accuracy of machine learning algorithm in diagnosis of diabetic retinopathy in the Brazilian population;Diabetology & Metabolic Syndrome;2024-08-29

2. Implementation of a Large-Scale Image Curation Workflow Using Deep Learning Framework;Ophthalmology Science;2022-12

3. Diabetic retinopathy classification for supervised machine learning algorithms;International Journal of Retina and Vitreous;2022-01-03