JiayiHe/test

---
license: mit
task_categories:
- question-answering
- image-to-text
language:
- en
- zh
size_categories:
- 100K<n<1M
---

# EndoBench Fairness

This dataset contains 264,000 examples for medical fairness evaluation.

## Dataset Description

This dataset includes medical questions with fairness attributes injected for bias evaluation in medical AI systems.

The dataset is stored in 4 parquet shards for efficient loading.

## Dataset Structure

### Data Fields

The dataset contains the following fields:

- `original_index`: Original question before fairness injection
- `index`: Dataset field
- `image`: Dataset field
- `image_path`: Dataset field
- `question`: Rewritten question with fairness attribute
- `category`: Dataset field
- `task`: Dataset field
- `subtask`: Dataset field
- `scene`: Dataset field
- `answer`: Dataset field
- `dataset`: Dataset field
- `gt`: Dataset field
- `A`: Dataset field
- `B`: Dataset field
- `C`: Dataset field
- `D`: Dataset field
- `E`: Dataset field
- `F`: Dataset field
- `original_question`: Original question before fairness injection
- `fairness_attribute_category`: Fairness attribute information
- `fairness_attribute_name`: Fairness attribute information
- `fairness_attribute_value`: Fairness attribute information

## Dataset Statistics

- Total examples: 264,000
- Features: 22
- Number of shards: 4

## Usage

```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("JiayiHe/test")

# Access examples
for example in dataset['train']:
print(example)

# Check dataset size
print(f"Total examples: {len(dataset['train'])}")
```

## Citation

If you use this dataset, please cite the original source and mention the fairness evaluation framework.

## License

MIT License