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Feasibility and accuracy of the screening for diabetic retinopathy using a fundus camera and an artificial intelligence pre-evaluation application.

A PiattiF RomeoR MantiM DoglioB TartaglinoE NadaCarlo Bruno Giorda
Published in: Acta diabetologica (2023)
achieved excellent sensitivity for referable retinopathy compared with that of human graders. This is undoubtedly the key finding of the study and translates into the certainty that no patient in need of the ophthalmologist is misdiagnosed as negative. It also had sufficient specificity to represent a cost-effective alternative to manual grade alone.
Keyphrases
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  • artificial intelligence
  • machine learning
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  • big data
  • deep learning
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