CMAP-Fusion Model Performance Comparison on COVID-19 and ISIC Datasets

Chong Liu published a 9.5 KB Excel file on figshare in April 2026. The data compares classification performance between a CMAP-Fusion model and baseline models on COVID-19 and ISIC datasets. Results include 95% confidence intervals.

Use Cases

• Benchmarking new classification models based on reported performance metrics
• Analyzing statistical significance of model results based on confidence intervals
• Comparing model efficacy across different medical imaging datasets

Strengths

• Performance metrics include 95% confidence intervals, providing statistical context
• Data is openly licensed under CC-BY-4.0

Limitations

• Row count is unknown, which may limit suitability assessment
• Column-level documentation is absent; field semantics must be inferred after download

Provenance

Source

figshare

Freshness

Last updated 2026-04-24 17:35:31; freshness should be verified