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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.

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Dataset Card

Dataset Card for MedQA

Dataset Subsets

This dataset contains multiple configs:

  • —QA with four possible answers (as reported in the paper)
  • —en: English instances
  • —tw: Taiwanese instances
  • —zh: Chinese instances
  • —xlang: instances in any language
  • —QA with five possible answers (the original datasets for English and Chinese)
  • —en_5
  • —zh_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:

questionanswermeta_infoanswer_idxABCDlanguage
A 23-year-old pregna...Nitrofurantoinstep2&3DAmpicillinCeftriaxoneDoxycyclineNitrofurantoinen

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}
}