You need to agree to share your contact information to access this dataset

This repository is publicly accessible, but you have to accept the conditions to access its files and content.

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.

Log in or Sign Up to review the conditions and access this dataset content.

✏️ 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")
Downloads last month
142