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---
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.
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