|
--- |
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dataset_info: |
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features: |
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- name: image_id |
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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 |
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data_files: |
|
- split: train |
|
path: data/train-* |
|
- split: validation |
|
path: data/validation-* |
|
- split: test |
|
path: data/test-* |
|
--- |
|
|
|
## Citation |
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|
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If you use the ROCOv2 dataset in your research, please cite the following paper: |
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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, |
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author = { {Ronan L.M.} }, |
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title = { ROCOv2-radiology (Revision 5d66908) }, |
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year = 2024, |
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url = { https://huggingface.co/datasets/eltorio/ROCOv2-radiology }, |
|
doi = { 10.57967/hf/3489 }, |
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publisher = { Hugging Face } |
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} |
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``` |
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## License |
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|
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The ROCOv2 dataset is licensed under the CC BY-NC-SA 4.0 license. |
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|
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## Acknowledgments |
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|
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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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|
