Model Performance Metrics for 5-Fold CV, Prospective and External Validation

A 5.5 KB Excel file containing model performance metrics, including area under the precision-recall curve (AUPRC). The dataset was authored by Yik-Shun Lin and last updated on May 5, 2026. It reports results from 5-fold cross-validation, prospective testing, and external validation.

Use Cases

• Compare model robustness based on performance across 5-fold cross-validation, prospective testing, and external validation.
• Benchmark AUPRC scores for models in similar domains based on the reported validation results.
• Analyze the generalization gap between internal cross-validation and external validation performance.
• Inform validation strategy selection for future projects based on the comparative results.

Strengths

• Performance metrics are reported for three distinct validation methods: 5-fold cross-validation, prospective testing, and external validation.
• Dataset is licensed under CC-BY-4.0, permitting sharing and adaptation.
• File size is 5.5 KB, indicating a concise and focused set of results.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

figshare

Freshness

Last updated 2026-05-05 17:37:19; freshness should be verified.