Automated diabetic retinopathy detection in smartphone-based fundus photography using artificial intelligence

OBJECTIVES: To assess the role of artificial intelligence (AI)-based automated software for detection of diabetic retinopathy (DR) and sight-threatening DR (STDR) by fundus photography taken using a smartphone-based device and validate it against ophthalmologist’s grading. METHODS: Three hundred and...

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Detalles Bibliográficos
Autores principales: Rajalakshmi, Ramachandran, Subashini, Radhakrishnan, Anjana, Ranjit Mohan, Mohan, Viswanathan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5997766/
https://www.ncbi.nlm.nih.gov/pubmed/29520050
http://dx.doi.org/10.1038/s41433-018-0064-9

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5997766/
https://www.ncbi.nlm.nih.gov/pubmed/29520050
http://dx.doi.org/10.1038/s41433-018-0064-9

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