Towards explainable deep neural networks for the automatic detection of diabetic retinopathy

HIGHLIGHTS

• who: Hanan Saleh Alghamdi from the Information Systems Department, Faculty of Computing and Information Technology, King Abdulaziz University have published the research work: Towards Explainable Deep Neural Networks for the Automatic Detection of Diabetic Retinopathy, in the Journal: (JOURNAL)
• what: The experiment showed that theon random ARETDB1 dataset to detect abnormalities in fundus images. that forest achieved a better classification accuracy of 93.58% thanThe the experiment Nau00efve Bayesshowed classifier, the random forest achieved a better accuracy of 93.58% than Nau00efve Bayes which reached 83.63%. The authors aim to compare these algorithms based . . .
  

   

  

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