Datasetpublic

YYama0/RR-Findings

RR-Findings: Chest CT Findings Labels for Japanese Radiology Reports RR-Findings is a labeled dataset of Japanese chest CT radiology reports derived from the MedNLP-SC Radiology Report TNM Staging (RR-TNM) Dataset, released as part of the NTCIR-17 MedNLP-SC shared task. A total of 243 Japanese radiology reports (covering 27 lung cancer cases, annotated independently by nine board-certified radiologists) were further enriched with multi-label chest CT findings assigned by… See the full description on the dataset page: https://huggingface.co/datasets/YYama0/RR-Findings.

sourceHugging Facecc-by-4.0updated 2mo agoView on Hugging Face

0likes30downloads

Dataset Card

RR-Findings: Chest CT Findings Labels for Japanese Radiology Reports

RR-Findings is a labeled dataset of Japanese chest CT radiology reports derived from the MedNLP-SC Radiology Report TNM Staging (RR-TNM) Dataset, released as part of the NTCIR-17 MedNLP-SC shared task.

A total of 243 Japanese radiology reports (covering 27 lung cancer cases, annotated independently by nine board-certified radiologists) were further enriched with multi-label chest CT findings assigned by radiology residents. All labels follow the schema of the CT-RATE dataset.

Labels

Each report is annotated with 18 clinically relevant chest CT findings:

Medical material  
Arterial wall calcification  
Cardiomegaly  
Pericardial effusion  
Coronary artery wall calcification  
Hiatal hernia  
Lymphadenopathy  
Emphysema  
Atelectasis  
Lung nodule  
Lung opacity  
Pulmonary fibrotic sequela  
Pleural effusion  
Mosaic attenuation pattern  
Peribronchial thickening  
Consolidation  
Bronchiectasis  
Interlobular septal thickening

The labeling schema is based on CT-RATE: https://huggingface.co/datasets/ibrahimhamamci/CT-RATE

Source Dataset

RR-Findings is built upon:

MedNLP-SC Radiology Report TNM Staging (RR-TNM) Dataset NTCIR-17 MedNLP-SC Shared Task 243 PHI-free Japanese radiology reports https://sociocom.naist.jp/download/mednlp-sc-rr-tnm/

Related Research and Citation

This dataset was developed as part of the following study:

@article{yamagishi2026modernber,
  title   = {ModernBERT is more efficient than conventional BERT for chest CT findings classification in Japanese radiology reports},
  author  = {Yamagishi, Yosuke and Kikuchi, Tomohiro and Hanaoka, Shouhei and Yoshikawa, Takeharu and Abe, Osamu},
  journal = {Scientific Reports},
  year    = {2026},
  volume  = {16},
  pages   = {15956},
  doi     = {10.1038/s41598-026-44292-z},
  url     = {https://doi.org/10.1038/s41598-026-44292-z}
}

If you use this dataset in your research or publication, please cite the paper above.

License

CC BY 4.0 You may use, modify, and redistribute the dataset with appropriate attribution.