Counterfactual Explanations for a Gallstone Prediction Model

Five counterfactual explanations generated by Prosenjit Das using the DiCE method for a CB classifier. The data demonstrates how variations in CRP and Vitamin D levels influence the Gallstone Status prediction for a single instance. The dataset was last updated on June 1, 2026.

Use Cases

• Illustrate the DiCE counterfactual explanation method based on the description of its use.
• Analyze feature sensitivity for a gallstone prediction model based on the described variations in CRP and Vitamin D.
• Benchmark counterfactual explanation tools based on the provided example output.
• Study the influence of specific biomarkers on a binary clinical outcome based on the features mentioned.

Strengths

• Dataset is small (5.5 KB), facilitating quick download and inspection.
• Released under a permissive CC-BY-4.0 license, allowing for broad reuse.
• Provides a concrete example of a specific interpretability method (DiCE) applied to a clinical prediction task.

Limitations

• The dataset contains only five rows, representing explanations for a single data instance.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

figshare

Collection Method

Generated using the DiCE (Diverse Counterfactual Explanations) method for a CB (Classifier) model.

Freshness

Last updated 2026-06-01 17:51:48; freshness should be verified.