---
title: med_qa
canonical_url: "https://www.modelscope.cn/datasets/AI-ModelScope/med_qa"
md_url: "https://www.modelscope.cn/datasets/AI-ModelScope/med_qa.md"
repository: AI-ModelScope/med_qa
chinese_name: med_qa
last_updated: 2025-01-17
license: "Apache License 2.0"
storage_size: "126 MB"
downloads: 2860
stars: 4
---

# med_qa

> med_qa - AI-ModelScope 在 ModelScope 开源的数据集。Dataset Card for MedQA

AI-ModelScope/med_qa 是 ModelScope 魔搭社区上的数据集，存储大小 126 MB，采用 Apache License 2.0 许可。

- **Repository**: AI-ModelScope/med_qa
- **License**: Apache License 2.0
- **Storage size**: 126 MB
- **Downloads**: 2860
- **Stars**: 4
- **Last updated**: 2025-01-17

Source: https://www.modelscope.cn/datasets/AI-ModelScope/med_qa

---

# Dataset Card for MedQA

## Dataset Description

- **Homepage:** https://github.com/jind11/MedQA
- **Pubmed:** False
- **Public:** True
- **Tasks:** QA


In this work, we present the first free-form multiple-choice OpenQA dataset for solving medical problems, MedQA,
collected from the professional medical board exams. It covers three languages: English, simplified Chinese, and
traditional Chinese, and contains 12,723, 34,251, and 14,123 questions for the three languages, respectively. Together
with the question data, we also collect and release a large-scale corpus from medical textbooks from which the reading
comprehension models can obtain necessary knowledge for answering the questions.



## Citation Information

```
@article{jin2021disease,
  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={Applied Sciences},
  volume={11},
  number={14},
  pages={6421},
  year={2021},
  publisher={MDPI}
}

```