---
dataset_info:
  features:
  - name: image_id
    dtype: string
  - name: caption
    dtype: string
  - name: cui
    sequence: string
  splits:
  - name: train
    num_bytes: 11668074
    num_examples: 59962
  - name: validation
    num_bytes: 2024347
    num_examples: 9904
  - name: test
    num_bytes: 2028034
    num_examples: 9927
  download_size: 7123511
  dataset_size: 15720455
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
---

## Citation

If you use the ROCOv2 dataset in your research, please cite the following paper:

Pelka, O., Menze, B. H., & Rexhausen, S. E. (2023). Radiology Objects in COntext version 2 (ROCOv2): A multimodal dataset for medical image analysis. 
arXiv preprint arXiv:2405.10004.

```latex
@misc {ronan_l.m._2024,
	author       = { {Ronan L.M.} },
	title        = { ROCOv2-radiology (Revision 5d66908) },
	year         = 2024,
	url          = { https://huggingface.co/datasets/eltorio/ROCOv2-radiology },
	doi          = { 10.57967/hf/3489 },
	publisher    = { Hugging Face }
}
```
## License

The ROCOv2 dataset is licensed under the CC BY-NC-SA 4.0 license.

## Acknowledgments

We acknowledge the National Library of Medicine (NLM) for providing access to the PMC Open Access Subset. We also acknowledge the creators of the Medical Concept Annotation Toolkit (MedCAT) for providing a valuable tool for concept extraction and annotation.