mathewhe/medqa
Dataset Card for MedQA Homepage: https://github.com/jind11/MedQA This is an unofficial curation of the MedQA dataset, uploaded here with minimal (i.e., no content-modifying) processing. Paper: What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams (MDPI) Languages: English (en), Taiwanese (tw), and Chinese (zh). Dataset Subsets This dataset contains multiple configs: QA with four possible answers (as… See the full description on the dataset page: https://huggingface.co/datasets/mathewhe/medqa.
Dataset Card for MedQA
- Homepage: https://github.com/jind11/MedQA
- This is an unofficial curation of the MedQA dataset, uploaded here with minimal (i.e., no content-modifying) processing.
- Paper: *What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams* (MDPI)
- Languages: English (en), Taiwanese (tw), and Chinese (zh).
Dataset Subsets
This dataset contains multiple configs:
- QA with four possible answers (as reported in the paper)
en: English instancestw: Taiwanese instanceszh: Chinese instancesxlang: instances in any language- QA with five possible answers (the original datasets for English and Chinese)
en_5zh_5
Data can be loaded by specifying the config and data split:
from datasets import load_dataset
data = load_dataset("mathewhe/medqa", "en", split="train")Possible splits are "train", "dev", and "test".
Dataset Structure
Each data subset will contain the following columns:
question (string): The question/prompt.
answer: The correct response.
answer_idx: The multiple-choice identifier for the correct response.
A: The "A" answer.
B: The "B" answer.
C: The "C" answer.
D: The "D" answer.
E (in `en_5` or `zh_5` subsets): The "E" answer.
language: "en", "tw", or "zh".Example from en-train:
Citation Information
For reproducibility, please include a link to this dataset when publishing results based on the included data.
For formal citations, please cite the original publication:
@article{jin2020disease,
title={What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams},
author={Jin, Di and Pan, Eileen and Oufattole, Nassim and Weng, Wei-Hung and Fang, Hanyi and Szolovits, Peter},
journal={arXiv preprint arXiv:2009.13081},
year={2020}
}