---
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](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](https://www.freecn.io/).
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
```python
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

```python
# 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

<!-- Provide the basic links for the model. -->

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