To validate the artificial intelligence subsystem of the DDART medical device for the automated detection of lesions compatible with diabetic retinopathy in a random sample of retinal fundus photographs.
Secondary Objectives To determine the sensitivity and specificity of the artificial intelligence subsystem for the detection of diabetic retinopathy.
To estimate the overall diagnostic accuracy and the area under the receiver operating characteristic (ROC) curve (AUC).
To compare the performance of the algorithm with that of experienced ophthalmologists.
To evaluate the ability of the model to distinguish between different stages of disease severity
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Participants that are able to provide consent for their fundus photograph to be recorded
Cohort
Cross-sectional
Color retinal fundus photograph
Diagnostic testDiagnostic Test: color fundus photograph Description: Color retinal fundus photographs will be acquired from: Digital non-mydriatic fundus cameras.
Validation the artificial intelligence subsystem of the DDART medical device for the automated detection of lesions compatible with diabetic retinopathy in a random sample of retinal fundus photographs.
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