A Comparative Study on Diabetic Retinopathy Datasets for Data Accuracy Detection

Diabetic retinopathy is a problem that affects diabetics' eyes. It has the potential to cause vision loss by affecting the small blood vessels in the rear of the eye as well as Diabetic retinopathy is difficult to detect and comprehend. Dataset 1 [15] had the highest accuracy of 0.74, followed...

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Bibliographic Details
Main Authors: Chaturvedi, Kapil, Bhandari, Vijay, Shrivastava, Ritu, Tiwari, Rishabh
Format: Conference Proceeding
Language:English
Subjects:
Accuracy
Comparative Analysis
Computational modeling
Computer science
Dataset Comparison
Dataset Evaluation
Diabetes
Diabetic retinopathy
Healthcare
Machine Learning
Medical services
Model Simplicity
Predictive models
Retina
Sensitivity
Transfer learning
Vision Loss
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Summary:Diabetic retinopathy is a problem that affects diabetics' eyes. It has the potential to cause vision loss by affecting the small blood vessels in the rear of the eye as well as Diabetic retinopathy is difficult to detect and comprehend. Dataset 1 [15] had the highest accuracy of 0.74, followed by Dataset 3 [17] at 0.72, and Dataset 2 [16] had the lowest accuracy of 0.68. The equal value of 3,989,285 indicates that all three datasets have the same model complexity or simplicity level. The use of algorithms in various datasets can provide a direction for picture classification work. progressively learn more about eye illnesses, these models need to continue to learn in order to remain accurate. Knowing about and tackling these issues are the most important first steps.
ISSN:2688-0288
DOI:10.1109/SCEECS61402.2024.10481879