README.md

metadata

extra_gated_prompt: >-
  Dataset from Shared task on Large-Scale Radiology Report Generation
  (https://stanford-aimi.github.io/RRG24/). Access requires a verified CITI
  training certificate using the same process outlined by PhysioNet (see
  https://physionet.org/about/citi-course/) Please provide proof via the
  verification URL, which takes the form
  https://www.citiprogram.org/verify/?XXXXXX. You agree to not use the model to
  conduct experiments that cause harm to human subjects.
extra_gated_fields:
  Full Name: text
  Email: text
  Affiliation: text
  CITI Certification Verification URL: text
  I agree to the DUA of bimcv-covid19: checkbox
  I agree to the DUA of mimic-cxr: checkbox
  I agree to the DUA of padchest: checkbox
  I agree to the DUA of candid-ptx: checkbox
  I agree to not redistribute or host cheXpert anywhere else: checkbox
dataset_info:
  features:
    - name: source
      dtype: string
    - name: images_path
      sequence: string
    - name: images
      sequence: image
    - name: impression
      dtype: string
    - name: findings
      dtype: string
  splits:
    - name: train
      num_bytes: 72889169962.96
      num_examples: 333205
    - name: validation
      num_bytes: 1885465464.459
      num_examples: 8543
  download_size: 74547230342
  dataset_size: 74774635427.419
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*

✏️ Citation

@inproceedings{xu-etal-2024-overview,
    title = "Overview of the First Shared Task on Clinical Text Generation: {RRG}24 and {\textquotedblleft}Discharge Me!{\textquotedblright}",
    author = "Xu, Justin  and
      Chen, Zhihong  and
      Johnston, Andrew  and
      Blankemeier, Louis  and
      Varma, Maya  and
      Hom, Jason  and
      Collins, William J.  and
      Modi, Ankit  and
      Lloyd, Robert  and
      Hopkins, Benjamin  and
      Langlotz, Curtis  and
      Delbrouck, Jean-Benoit",
    editor = "Demner-Fushman, Dina  and
      Ananiadou, Sophia  and
      Miwa, Makoto  and
      Roberts, Kirk  and
      Tsujii, Junichi",
    booktitle = "Proceedings of the 23rd Workshop on Biomedical Natural Language Processing",
    month = aug,
    year = "2024",
    address = "Bangkok, Thailand",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2024.bionlp-1.7/",
    doi = "10.18653/v1/2024.bionlp-1.7",
    pages = "85--98",
}

Interpret-CXR: A Large-scale Collection of CXR datasets.

📝 Paper • 🤗 Hugging Face • 🧩 Github • 🪄 Project

✨ Latest News

• [02/20/2024]: Shared task at BioNLP@ACL2024 online [Website].

💡 Motivation

We curated the "Interpret-CXR" dataset for the following motivations:

• For the shared task on large-scale radiology report generation at BioNLP@ACL2024.
• Simplify the data access process.
• Standardize the benchmark for future research in this field

🎬 Get Started

from datasets import load_dataset

dataset = load_dataset("StanfordAIMI/interpret-cxr-public")