metadata

license: apache-2.0
configs:
  - config_name: english-full
    data_files:
      - split: train
        path: english/train.jsonl
      - split: test
        path: english/test.jsonl
  - config_name: english-qi
    data_files:
      - split: train
        path: english/qi_train.jsonl
      - split: test
        path: english/qi_test.jsonl
  - config_name: english-dp
    data_files:
      - split: train
        path: english/dp_train.jsonl
      - split: test
        path: english/dp_test.jsonl
  - config_name: english-custom
    data_files:
      - split: train
        path: english/custom_train.jsonl
      - split: test
        path: english/custom_test.jsonl
  - config_name: french-full
    data_files:
      - split: train
        path: french/train.jsonl
      - split: test
        path: french/test.jsonl
  - config_name: french-qi
    data_files:
      - split: train
        path: french/qi_train.jsonl
      - split: test
        path: french/qi_test.jsonl
  - config_name: french-dp
    data_files:
      - split: train
        path: french/dp_train.jsonl
      - split: test
        path: french/dp_test.jsonl
  - config_name: french-custom
    data_files:
      - split: train
        path: french/custom_train.jsonl
      - split: test
        path: french/custom_test.jsonl
task_categories:
  - multiple-choice
language:
  - fr
  - en
tags:
  - medical question answering
pretty_name: ecn-qa

Model Card for Raidium ECN-QA

The dataset is introduced in the paper "Efficient Medical Question Answering with Knowledge-Augmented Question Generation".

Paper: https://arxiv.org/abs/2405.14654

Dataset Details

Dataset Description

The dataset contains medical questions of different types. It was built from passed ECN exams (french medical examination) and questions created by FreeCN. The questions can be:

IQ (individual question) containing a question and several propositions that can be right or wrong
Custom which are IQ created by FreeCN
PQ (progressive questions) containing a case with an introduction and several following questions with multiple propositions

There are two versions of this dataset: the french and the english versions. The french split is the original dataset version.

Use this dataset

To access the full dataset in french or english

from datasets import load_dataset

# Login using e.g. `huggingface-cli login` to access this dataset
ds_french = load_dataset("raidium/ECN-QA", "french-full")
ds_english = load_dataset("raidium/ECN-QA", "english-full")

You can also access subsets of the dataset

# French version
ds_french_qi = load_dataset("raidium/ECN-QA", "french-qi")
ds_french_dp = load_dataset("raidium/ECN-QA", "french-dp")
ds_french_custom = load_dataset("raidium/ECN-QA", "french-custom")
# English version
ds_english_qi = load_dataset("raidium/ECN-QA", "english-qi")
ds_english_dp = load_dataset("raidium/ECN-QA", "english-dp")
ds_english_custom = load_dataset("raidium/ECN-QA", "english-custom")

Developed by: Raidium
License: Apache 2.0

Warnings

Some questions require images to be answered. They have not been filtered out in this dataset, to it is impossible to get 100% accuracy on this dataset.
The english version is an automated translation (using Azure Translation api), hence, it might contain translation errors.

Dataset Sources

Repository: [https://github.com/raidium-med/MQG]
Paper: https://arxiv.org/abs/2405.14654

Citation

BibTeX:

@article{khlaut2024efficient,
  title={Efficient Medical Question Answering with Knowledge-Augmented Question Generation},
  author={Khlaut, Julien and Dancette, Corentin and Ferreres, Elodie and Bennani, Alaedine and H{\'e}rent, Paul and Manceron, Pierre},
  journal={Clinical NLP Workshop, NAACL 2024},
  year={2024}
}

Dataset Card Contact

julien.khlaut at raidium.fr