Retinal G1020: CAD Model Effectiveness Results

5.5 KB of results from evaluating a Computer-Aided Diagnosis model on the Retinal G1020 dataset. The data, authored by Debendra Muduli and last updated in May 2026, likely contains performance metrics from a 10x5-fold cross-validation approach using a Grey Wolf Optimizer and Extreme Learning Machine. The small file size suggests a focused set of evaluation scores rather than raw image data.

Use Cases

• Benchmarking CAD model performance based on the described 10x5-fold cross-validation results.
• Comparing optimization algorithms (GWO) and classifier architectures (ELM) for retinal image analysis.
• Validating model effectiveness metrics for potential clinical deployment in diagnostic tools.

Strengths

• The dataset is openly shared under a CC-BY-4.0 license, facilitating reuse.
• It provides a specific, documented evaluation methodology (10x5-fold cross-validation with GWO+ELM).

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The 5.5 KB size indicates a very limited scope, likely containing only summary results.

Provenance

Source

figshare

Collection Method

Likely contains derived performance metrics from model evaluation.

Freshness

Last updated 2026-05-04 17:50:47; freshness should be verified.