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MedMCQA

Tasks:
Multiple Choice
Question Answering
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100K - 1M
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metadata 
dataset_info:
  - config_name: conversational
    features:
      - name: id
        dtype: string
      - name: prompt
        list:
          - name: role
            dtype: string
          - name: content
            dtype: string
      - name: completion
        list:
          - name: role
            dtype: string
          - name: content
            dtype: string
      - name: Label
        dtype: string
    splits:
      - name: train
        num_bytes: 125768683
        num_examples: 182822
      - name: dev
        num_bytes: 2950917
        num_examples: 4183
      - name: test
        num_bytes: 3894526
        num_examples: 6150
    download_size: 36295736
    dataset_size: 132614126
  - config_name: processed
    features:
      - name: Question
        dtype: string
      - name: Explanation
        dtype: string
      - name: Option_A
        dtype: string
      - name: Option_B
        dtype: string
      - name: Option_C
        dtype: string
      - name: Option_D
        dtype: string
      - name: id
        dtype: string
      - name: Label
        dtype: string
    splits:
      - name: train
        num_bytes: 124419306
        num_examples: 182822
      - name: dev
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        num_examples: 4183
      - name: test
        num_bytes: 1201595
        num_examples: 6150
    download_size: 86571328
    dataset_size: 127710579
  - config_name: source
    features:
      - name: question
        dtype: string
      - name: exp
        dtype: string
      - name: cop
        dtype: int64
      - name: opa
        dtype: string
      - name: opb
        dtype: string
      - name: opc
        dtype: string
      - name: opd
        dtype: string
      - name: subject_name
        dtype: string
      - name: topic_name
        dtype: string
      - name: id
        dtype: string
      - name: choice_type
        dtype: string
    splits:
      - name: train
        num_bytes: 131903307
        num_examples: 182822
      - name: dev
        num_bytes: 2221428
        num_examples: 4183
      - name: test
        num_bytes: 1400888
        num_examples: 6150
    download_size: 87908602
    dataset_size: 135525623
configs:
  - config_name: conversational
    data_files:
      - split: train
        path: conversational/train-*
      - split: dev
        path: conversational/dev-*
      - split: test
        path: conversational/test-*
  - config_name: processed
    data_files:
      - split: train
        path: processed/train-*
      - split: dev
        path: processed/dev-*
      - split: test
        path: processed/test-*
  - config_name: source
    data_files:
      - split: train
        path: source/train-*
      - split: dev
        path: source/dev-*
      - split: test
        path: source/test-*
license: cc-by-sa-4.0
task_categories:
  - multiple-choice
  - question-answering
language:
  - en
pretty_name: MedMCQA
size_categories:
  - 100K<n<1M
tags:
  - medical

MedMCQA : A Large-scale Multi-Subject Multi-Choice Dataset for Medical domain Question Answering

Dataset Description

Links
Homepage: Github.io
Repository: Github
Paper: arXiv
Leaderboard: Papers with Code
Contact (Original Authors): Aaditya Ura aadityaura@gmail.com), Logesh logesh.umapathi@saama.com
Contact (Curator): Artur Guimarães (artur.guimas@gmail.com)

Dataset Summary

`MedMCQA has more than 194k high-quality AIIMS & NEET PG entrance exam MCQs covering 2.4k healthcare topics and 21 medical subjects are collected with an average token length of 12.77 and high topical diversity.

Each sample contains a question, correct answer(s), and other options which require a deeper language understanding as it tests the 10+ reasoning abilities of a model across a wide range of medical subjects & topics. A detailed explanation of the solution, along with the above information, is provided in this study.

MedMCQA provides an open-source dataset for the Natural Language Processing community. It is expected that this dataset would facilitate future research toward achieving better QA systems.`

Data Instances

Source Format 

{
    "question":"A 40-year-old man presents with 5 days of productive cough and fever. Pseudomonas aeruginosa is isolated from a pulmonary abscess. CBC shows an acute effect characterized by marked leukocytosis (50,000 mL) and the differential count reveals a shift to left in granulocytes. Which of the following terms best describes these hematologic findings?",
    "exp": "Circulating levels of leukocytes and their precursors may occasionally reach very high levels (>50,000 WBC mL). These extreme elevations are sometimes called leukemoid reactions because they are similar to the white cell counts observed in leukemia, from which they must be distinguished. The leukocytosis occurs initially because of the accelerated release of granulocytes from the bone marrow (caused by cytokines, including TNF and IL-1) There is a rise in the number of both mature and immature neutrophils in the blood, referred to as a shift to the left. In contrast to bacterial infections, viral infections (including infectious mononucleosis) are characterized by lymphocytosis Parasitic infestations and certain allergic reactions cause eosinophilia, an increase in the number of circulating eosinophils. Leukopenia is defined as an absolute decrease in the circulating WBC count.",
    "cop":1,
    "opa":"Leukemoid reaction",
    "opb":"Leukopenia",
    "opc":"Myeloid metaplasia",
    "opd":"Neutrophilia",
    "subject_name":"Pathology",
    "topic_name":"Basic Concepts and Vascular changes of Acute Inflammation",
    "id":"4e1715fe-0bc3-494e-b6eb-2d4617245aef",
    "choice_type":"single"
}

Data Fields

Source Format

  • id : a string question identifier for each example
  • question : question text (a string)
  • opa : Option A
  • opb : Option B
  • opc : Option C
  • opd : Option D
  • cop : Correct option (Answer of the question)
  • choice_type : Question is single-choice or multi-choice
  • exp : Expert's explanation of the answer
  • subject_name : Medical Subject name of the particular question
  • topic_name : Medical topic name from the particular subject

Data Splits

TO:DO

Additional Information

Dataset Curators

Original Paper

Huggingface Curator

Licensing Information

CC BY-SA 4.0

Citation Information 

@InProceedings{pmlr-v174-pal22a,
  title = 	 {MedMCQA: A Large-scale Multi-Subject Multi-Choice Dataset for Medical domain Question Answering},
  author =       {Pal, Ankit and Umapathi, Logesh Kumar and Sankarasubbu, Malaikannan},
  booktitle = 	 {Proceedings of the Conference on Health, Inference, and Learning},
  pages = 	 {248--260},
  year = 	 {2022},
  editor = 	 {Flores, Gerardo and Chen, George H and Pollard, Tom and Ho, Joyce C and Naumann, Tristan},
  volume = 	 {174},
  series = 	 {Proceedings of Machine Learning Research},
  month = 	 {07--08 Apr},
  publisher =    {PMLR},
  pdf = 	 {https://proceedings.mlr.press/v174/pal22a/pal22a.pdf},
  url = 	 {https://proceedings.mlr.press/v174/pal22a.html},
}

10.1016/j.patter.2022.100445

Contributions

Thanks to araag2 for adding this dataset.