Performance Comparison of CNN and Vision Transformer Models for Lung Cancer Classification

A performance comparison of various Convolutional Neural Network (CNN) architectures and a Vision Transformer (ViT) model on a lung cancer classification task. The dataset is 5.5 KB in size, authored by Nayab Asim, and was last updated on June 2, 2026. It is shared under a CC-BY-4.0 license on figshare.

Use Cases

• Benchmarking CNN architectures against Vision Transformers based on the described performance comparison.
• Informing model selection for lung cancer classification tasks based on the reported results.
• Reproducing or validating comparative studies in medical imaging AI.

Strengths

• Dataset is small (5.5 KB), facilitating quick download and inspection.
• Explicitly compares modern architectures like Vision Transformers with CNNs for a specific medical task.
• Shared under a permissive CC-BY-4.0 license.

Limitations

• The dataset is extremely small (5.5 KB), suggesting it contains only summary results, not the underlying image data or model weights.
• Row count and column-level documentation are unknown, limiting detailed analysis of the comparison methodology.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

figshare

Freshness

Last updated 2026-06-02 17:34:55; freshness should be verified.