README.md

metadata

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

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

@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}
}