FrenchMedMCQA is the first publicly available Multiple-Choice Question Answering (MCQA) dataset in French for medical domain. It is composed of 3,105 questions taken from real exams of the French medical specialization diploma in pharmacy, mixing single and multiple answers.
| Links | |
|---|---|
| Homepage: | https://github.com/qanastek/FrenchMedMCQA |
| Repository: | https://github.com/qanastek/FrenchMedMCQA |
| Paper: | https://hal.archives-ouvertes.fr/hal-03824241v1 |
| Leaderboard: | https://paperswithcode.com/dataset/frenchmedmcqa |
| Point of Contact: | Yanis LABRAK |
FrenchMedMCQA is the first open-source Multiple-Choice Question Answering (MCQA) dataset which propose questions with a single or multiple answer(s) based on real-world medical exam questions.
To collect the dataset mentioned in the paper, please follow the below steps :
./spiders/ by using cd ./spiders/pip3 install -r requirements.txtbash ./run_scrapping.sh./corpus/./corpus_csv/multiple-choice-QA , open-domain-QA: The dataset can be used to train a model for multi-choice questions answering, open domain questions answering.
The questions on these exams are difficult and often necessitate a deeper domain and language comprehension.
The questions and answers are available in French.
Example of a question with multiple answers :
{
"id": "6979d46501a3270436d37b98cf351439fbcbec8d5890d293dabfb8f85f723904",
"question": "Cocher la (les) proposition(s) exacte(s) : Le métronidazole :",
"answers": {
"a": "Est un dérivé du pyrazole",
"b": "Peut induire un effet antabuse",
"c": "Peut être administré par voie parentérale intraveineuse",
"d": "Peut être utilisé dans certaines parasitoses à protozoaires",
"e": "Est inefficace dans les infections à germes anaérobies"
},
"correct_answers": [
"b",
"c",
"d"
],
}
id : Question identifierquestion : Question textanswers : The list of 5 options from A to Ecorrect_answers : Correct option(s) (Can be one or more answer(s) to the question)Globally, 70 % of the questions are kept for the train, 10 % for validation and last 20 % for testing.
The distribution of the subsets according to the number of answers are as follow :
| # Answers | Training | Validation | Test | Total |
|---|---|---|---|---|
| 1 | 595 | 164 | 321 | 1,080 |
| 2 | 528 | 45 | 97 | 670 |
| 3 | 718 | 71 | 141 | 930 |
| 4 | 296 | 30 | 56 | 382 |
| 5 | 34 | 2 | 7 | 43 |
| Total | 2171 | 312 | 622 | 3,105 |
We would very much appreciate it if you cite our publications :
@unpublished{labrak:hal-03824241,
TITLE = {{FrenchMedMCQA: A French Multiple-Choice Question Answering Dataset for Medical domain}},
AUTHOR = {Labrak, Yanis and Bazoge, Adrien and Dufour, Richard and Daille, B{\'e}atrice and Gourraud, Pierre-Antoine and Morin, Emmanuel and Rouvier, Mickael},
URL = {https://hal.archives-ouvertes.fr/hal-03824241},
NOTE = {working paper or preprint},
YEAR = {2022},
MONTH = Oct,
PDF = {https://hal.archives-ouvertes.fr/hal-03824241/file/LOUHI_2022___QA-3.pdf},
HAL_ID = {hal-03824241},
HAL_VERSION = {v1},
}
Python
100.0%
FrenchMedMCQA is the first publicly available Multiple-Choice Question Answering (MCQA) dataset in French for medical domain. It is composed of 3,105 questions taken from real exams of the French medical specialization diploma in pharmacy, mixing single and multiple answers.
| Links | |
|---|---|
| Homepage: | https://github.com/qanastek/FrenchMedMCQA |
| Repository: | https://github.com/qanastek/FrenchMedMCQA |
| Paper: | https://hal.archives-ouvertes.fr/hal-03824241v1 |
| Leaderboard: | https://paperswithcode.com/dataset/frenchmedmcqa |
| Point of Contact: | Yanis LABRAK |
FrenchMedMCQA is the first open-source Multiple-Choice Question Answering (MCQA) dataset which propose questions with a single or multiple answer(s) based on real-world medical exam questions.
To collect the dataset mentioned in the paper, please follow the below steps :
./spiders/ by using cd ./spiders/pip3 install -r requirements.txtbash ./run_scrapping.sh./corpus/./corpus_csv/multiple-choice-QA , open-domain-QA: The dataset can be used to train a model for multi-choice questions answering, open domain questions answering.
The questions on these exams are difficult and often necessitate a deeper domain and language comprehension.
The questions and answers are available in French.
Example of a question with multiple answers :
{
"id": "6979d46501a3270436d37b98cf351439fbcbec8d5890d293dabfb8f85f723904",
"question": "Cocher la (les) proposition(s) exacte(s) : Le métronidazole :",
"answers": {
"a": "Est un dérivé du pyrazole",
"b": "Peut induire un effet antabuse",
"c": "Peut être administré par voie parentérale intraveineuse",
"d": "Peut être utilisé dans certaines parasitoses à protozoaires",
"e": "Est inefficace dans les infections à germes anaérobies"
},
"correct_answers": [
"b",
"c",
"d"
],
}
id : Question identifierquestion : Question textanswers : The list of 5 options from A to Ecorrect_answers : Correct option(s) (Can be one or more answer(s) to the question)Globally, 70 % of the questions are kept for the train, 10 % for validation and last 20 % for testing.
The distribution of the subsets according to the number of answers are as follow :
| # Answers | Training | Validation | Test | Total |
|---|---|---|---|---|
| 1 | 595 | 164 | 321 | 1,080 |
| 2 | 528 | 45 | 97 | 670 |
| 3 | 718 | 71 | 141 | 930 |
| 4 | 296 | 30 | 56 | 382 |
| 5 | 34 | 2 | 7 | 43 |
| Total | 2171 | 312 | 622 | 3,105 |
We would very much appreciate it if you cite our publications :
@unpublished{labrak:hal-03824241,
TITLE = {{FrenchMedMCQA: A French Multiple-Choice Question Answering Dataset for Medical domain}},
AUTHOR = {Labrak, Yanis and Bazoge, Adrien and Dufour, Richard and Daille, B{\'e}atrice and Gourraud, Pierre-Antoine and Morin, Emmanuel and Rouvier, Mickael},
URL = {https://hal.archives-ouvertes.fr/hal-03824241},
NOTE = {working paper or preprint},
YEAR = {2022},
MONTH = Oct,
PDF = {https://hal.archives-ouvertes.fr/hal-03824241/file/LOUHI_2022___QA-3.pdf},
HAL_ID = {hal-03824241},
HAL_VERSION = {v1},
}
Python
100.0%