datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
MedQA-USMLE-4-optionsOriginal dataset introduced by Jin et al. in What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams
Citation information:
@article{jin2020disease,
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={arXiv preprint arXiv:2009.13081},
year={2020}
}
MedQA-USMLE-4-options-hfOriginal dataset introduced by Jin et al. in What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams
Citation information:
@article{jin2020disease,
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={arXiv preprint arXiv:2009.13081},
year={2020}
}
usmle-step1-form31
USMLE Step 1 — Form 31, Form 30 & NBME Form 27
Structured multiple-choice questions extracted from USMLE Step 1 and NBME practice forms.
Files
data/questions.jsonl — 183 USMLE Step 1 Form 31 questions (35 SOTA-cropped images)
questions_nbme27.jsonl — 198 NBME Form 27 questions (41 SOTA-cropped images)
questions_form30.jsonl — 200 NBME Form 30 questions (45 SOTA-cropped images)
Structure
Each record contains:
id — unique identifier (e.g. form31_page-0… See the full description on the dataset page: https://huggingface.co/datasets/agentN0/usmle-step1-form31.MedQA-USMLE-4-options
Mirrored by Aurigene AI
Discovery stage: Evidence and literature
US Medical Licensing Exam style questions in four-option multiple choice form.
Rows: 11,451 (phrases_no_exclude_test.jsonl 1,273, phrases_no_exclude_train.jsonl 10,178)
Pairs with Aurigene-AI/BioMistral-7B from our model catalogue.
Upstream: GBaker/MedQA-USMLE-4-options - all credit to the original authors and to the researchers who produced the underlying data; the dataset card and licence below are theirs.… See the full description on the dataset page: https://huggingface.co/datasets/Aurigene-AI/MedQA-USMLE-4-options.usmle-step1-qbank-v3MedQA-USMLE-Benchmark
💻 Dataset Usage
Run the following command to load the testing set (1,273 examples):
from datasets import load_dataset
dataset = load_dataset("shuyuej/MedQA-USMLE-Benchmark", split="test")
print(dataset)
MedQA-USMLE-4-options-hfMedQA-USMLE-4-optionsOriginal dataset introduced by Jin et al. in What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams
Citation information:
@article{jin2020disease,
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={arXiv preprint arXiv:2009.13081},
year={2020}
}
MedQA-USMLE-4-optionsOriginal dataset introduced by Jin et al. in What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams
Citation information:
@article{jin2020disease,
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={arXiv preprint arXiv:2009.13081},
year={2020}
}
MedQA-USMLE-4-options-hfOriginal dataset introduced by Jin et al. in What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams
Citation information:
@article{jin2020disease,
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={arXiv preprint arXiv:2009.13081},
year={2020}
}
MedQA-USMLE-4-optionsOriginal dataset introduced by Jin et al. in What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams
Citation information:
@article{jin2020disease,
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={arXiv preprint arXiv:2009.13081},
year={2020}
}
MedQA_USMLEMedQA-USMLE-4-optionsOriginal dataset introduced by Jin et al. in What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams
Citation information:
@article{jin2020disease,
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={arXiv preprint arXiv:2009.13081},
year={2020}
}
USMLE_fullusmle
USMLE Questions Dataset
Evaluation dataset of USMLE-style multiple choice questions.
Dataset structure
Each row has:
question: Question statement
options: List of options (e.g. ["(A) ...", "(B) ...", ...])
correct_answer: Correct option letter (A–E)
Loading
from datasets import load_dataset
ds = load_dataset("prapaa/usmle", data_files="{"train": "train.jsonl"}, split="train")
USMLE