Model Configuration for Heart Disease Dataset: UCI Benchmark with 303 Samples

Model configuration details for a deep learning framework evaluated on the UCI Heart Disease dataset. The dataset contains 303 samples and 13 clinical features. Author Vijay U. Rathod published the configuration on figshare under a CC-BY-4.0 license, with a last update recorded as 2026-05-08.

Use Cases

• Benchmarking model performance for heart disease prediction based on the 13 clinical features mentioned in the description
• Implementing a modular deep learning framework for heterogeneous clinical datasets based on the described architecture
• Studying the effect of dataset characteristics like sample size and class imbalance on model selection
• Reproducing the experimental results for heart disease prediction, which achieved an AUC of 0.8980

Strengths

• The framework was evaluated on a well-known benchmark dataset (UCI Heart Disease) with 303 samples and 13 features
• Experimental results are provided, including a specific AUC score of 0.8980 (±0.0483) for heart disease prediction
• The methodology includes robust preprocessing, fold-safe feature selection, and nested cross-validation as described

Limitations

• The dataset is very small at 5.5 KB, indicating limited scope and likely containing only configuration or summary data, not the full raw datasets
• Column-level documentation is absent; field semantics must be inferred after download
• Row count for the configuration data is unknown, which may limit suitability assessment

Provenance

Source

figshare, author Vijay U. Rathod

Collection Method

Likely generated as part of a research study proposing a unified deep learning framework.

Time Range

The configuration is associated with a study referencing benchmark datasets, but no specific temporal coverage for the underlying UCI data is provided.

Freshness

Last updated 2026-05-08 17:34:17; freshness should be verified as the date is in the future relative to the current time.

Geography

The UCI Heart Disease dataset's geographic origin is not specified in the provided description.