Deep Learning Model Performance Comparison for Papillary Thyroid Carcinoma

9.5 KB Excel file uploaded by Huiting Chen on figshare in April 2026. The data likely contains performance metrics from a comparison of deep learning and radiomics models for analyzing papillary thyroid carcinoma. The platform tags suggest the study involved internal and external validation cohorts.

Use Cases

• Benchmarking deep learning models against radiomics models based on the performance comparison described.
• Assessing model performance metrics like Net Reclassification Improvement (NRI) and Integrated Discrimination Improvement (IDI) mentioned in the platform tags.
• Validating predictive models for primary thyroid tumors using the internal and external validation cohorts referenced.
• Comparing the performance of a 'Vit Model' against other architectures as suggested by the platform tags.

Strengths

• File size is precisely 9.5 KB, indicating a compact, focused dataset.
• License is clearly defined as CC-BY-4.0, allowing for open reuse.
• Last update timestamp is provided (2026-04-03 17:43:09).

Limitations

• Row count and column definitions are unknown, limiting suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.
• The dataset is very small (9.5 KB), indicating limited scope and likely a summary of results rather than raw data.

Provenance

Source

figshare, uploaded by author Huiting Chen.

Collection Method

Likely results from a medical imaging research study comparing model performance.

Time Range

null

Freshness

Last updated 2026-04-03 17:43:09; freshness should be verified.

Geography

null