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--- |
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license: apache-2.0 |
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task_categories: |
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- question-answering |
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- multiple-choice |
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language: |
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- en |
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tags: |
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- medical |
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- healthcare |
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- mcqa |
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- entrance-exam |
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size_categories: |
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- 100K<n<1M |
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--- |
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# MedMCQA MCQA Dataset |
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This dataset contains the MedMCQA dataset converted to Multiple Choice Question Answering (MCQA) format. |
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## Dataset Description |
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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. |
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## Dataset Structure |
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Each example contains: |
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- `question`: The medical question |
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- `choices`: List of 4 possible answers (A, B, C, D) |
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- `answer_index`: Index of the correct answer (0-3) |
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- `answer_text`: Text of the correct answer |
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- `source`: Dataset source ("medmcqa") |
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- `explanation`: Detailed explanation including subject and topic information |
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## Data Splits |
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- Train: 182822 examples |
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- Validation: 4183 examples (Test split skipped - no labels available) |
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## Usage |
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```python |
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from datasets import load_dataset |
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dataset = load_dataset("RikoteMaster/medmcqa-mcqa") |
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``` |
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## Original Dataset |
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This dataset is based on the MedMCQA dataset: |
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- Paper: https://arxiv.org/abs/2203.14371 |
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- Original repository: https://huggingface.co/datasets/openlifescienceai/medmcqa |
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## Citation |
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```bibtex |
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@misc{pal2022medmcqa, |
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title={MedMCQA : A Large-scale Multi-Subject Multi-Choice Dataset for Medical domain Question Answering}, |
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author={Ankit Pal and Logesh Kumar Umapathi and Malaikannan Sankarasubbu}, |
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year={2022}, |
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eprint={2203.14371}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |
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``` |
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