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RadNLP/RadNLP2024_main_task

RadNLP 2024 main task: Document Classification for Lung Cancer Staging 📜 Paper 📚 Introduction RadNLP 2024 is a shared task in the international conference NTCIR-18, organized by the National Institute of Informatics in Japan. Management of lung cancer is based on the stage, and radiology reports provide various related information by describing medical images such as CT and MRI. However, radiology reports do not always specify the stage… See the full description on the dataset page: https://huggingface.co/datasets/RadNLP/RadNLP2024_main_task.

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RadNLP 2024 main task: Document Classification for Lung Cancer Staging

<p align="center"> <a href="https://sociocom.naist.jp/radnlp-2024/"> <img src="https://sociocom.naist.jp/radnlp-2024/wp-content/uploads/sites/11/2024/06/radnlp2024topimgsmall.png" alt="RadNLP 2024 logo"> </a> </p> <p align="center"> <a href="https://research.nii.ac.jp/ntcir/workshop/OnlineProceedings18/pdf/ntcir/01-NTCIR18-OV-RADNLP-NakamuraY.pdf">📜 Paper</a> </p>

📚 Introduction

RadNLP 2024 is a shared task in the international conference NTCIR-18, organized by the National Institute of Informatics in Japan.

Management of lung cancer is based on the stage, and radiology reports provide various related information by describing medical images such as CT and MRI.

However, radiology reports do not always specify the stage explicitly¹. This imposes extra workload on human experts for careful manual information extraction, which can be aided by automation.

Main task is a multi-label document classification to correctly determine T, N, and M categories for each radiology report.

—T category - Assessment of the size and/or extension of the primary lesion. Available choices: T0, Tis, T1mi, T1a, T1b, T1c, T2a, T2b, T3, T4
—N category - Assessment of the extent of lymph node metastasis. Available choices: N0, N1, N2, N3
—M category - Assessment of the extent of distant metastasis. Available choices: M0, M1a, M1b, M1c

In RadNLP 2024, we follow the staging criteria by the Japan Lung Cancer Society (JLCS). Note that the JLCS criteria closely aligns the global standard, namely the 8th edition of the TNM Classification of Malignant Tumours by the Union for International Cancer Control (UICC).

All radiology reports in RadNLP 2024 diagnose lung cancer at the initial evaluation. There are no reports of lung cancer post-treatment evaluation or different cancer.

Our datasets contain NO personal health information. The radiology reports are not derived from real medical institutions but are created with crowdsourcing by diagnosing de-identified images on Radiopaedia. Task participants requires no complex applications to use our datasets.

📊 Dataset Size & Format

This repository contains 6 files:

Language	Split	Number of radiology reports
English	Training	108
English	Validation	54
English	Test	81
English	Total	243
Japanese	Training	108
Japanese	Validation	54
Japanese	Test	216
Japanese	Total	378

Each file contains 5 columns:

Column	Type	Description
`id`	int	Unique identifier
`text`	string	Radiology Report
`t`	string	Gold standard for the T category
`n`	string	Gold standard for the N category
`m`	string	Gold standard for the M category

📖 Citation

If you find our work useful, please consider citing:

bibtex

@inproceedings{radnlp2024,
  title={NTCIR-18 RadNLP 2024 Overview: Dataset and Solutions for Automated Lung Cancer Staging},
  author={Nakamura, Yuta and Fujimoto, Koji and Kluckert, Jonas and Krauthammer, Michael and Kanzawa, Jun and Katayama, Akira and Kikuchi, Tomohiro and Kurokawa, Ryo and Gonoi, Wataru and Tashiro, Yuki and Hanaoka, Shouhei and Yada, Shuntaro and Aramaki, Eiji},
  year={2025},
  booktitle={NTCIR-18: Proceedings of the 18th NTCIR Conference on Evaluation ofInformation Access Technologies},
  doi={10.20736/0002002061}
}

📜 License

This project is licensed under the CC-BY-4.0 license.