---
license: apache-2.0
task_categories:
- question-answering
- multiple-choice
language:
- en
tags:
- medical
- healthcare
- mcqa
- entrance-exam
size_categories:
- 100K<n<1M
---

# MedMCQA MCQA Dataset

This dataset contains the MedMCQA dataset converted to Multiple Choice Question Answering (MCQA) format.

## Dataset Description

MedMCQA is a large-scale, Multiple-Choice Question Answering (MCQA) dataset designed to address real-world medical entrance exam questions. It covers various medical subjects and topics, making it ideal for evaluating AI systems on medical knowledge.

## Dataset Structure

Each example contains:
- `question`: The medical question
- `choices`: List of 4 possible answers (A, B, C, D)
- `answer_index`: Index of the correct answer (0-3)
- `answer_text`: Text of the correct answer
- `source`: Dataset source ("medmcqa")
- `explanation`: Detailed explanation including subject and topic information

 ## Data Splits
 
 - Train: 182822 examples
 - Validation: 4183 examples (Test split skipped - no labels available)

## Usage

```python
from datasets import load_dataset

dataset = load_dataset("RikoteMaster/medmcqa-mcqa")
```

## Original Dataset

This dataset is based on the MedMCQA dataset:
- Paper: https://arxiv.org/abs/2203.14371
- Original repository: https://huggingface.co/datasets/openlifescienceai/medmcqa

## Citation

```bibtex
@misc{pal2022medmcqa,
    title={MedMCQA : A Large-scale Multi-Subject Multi-Choice Dataset for Medical domain Question Answering}, 
    author={Ankit Pal and Logesh Kumar Umapathi and Malaikannan Sankarasubbu},
    year={2022},
    eprint={2203.14371},
    archivePrefix={arXiv},
    primaryClass={cs.CL}
}
```