根据《MedMCQA:面向医学领域问题回答的大规模多学科多选题数据集》（Pal等），MedMCQA是一个“多选题回答（MCQA）数据集，旨在解决现实世界中的医学入学考试问题”。该数据集“收集了超过194k个高质量的AIIMS和NEET PG入学考试的MCQ，涵盖了2.4k个医疗主题和21个医学科目，平均标记长度为12.77，主题多样性高。”

以下是数据集中的一个例子：

问题：在心脏病患者中，牙齿拔除术的抗生素预防是：A. 阿莫西林。B. 亚胺培南。C. 庆大霉素。D. 红霉素。答案：A

论文： https://arxiv.org/abs/2203.14371 代码： https://github.com/MedMCQA/MedMCQA

@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},
  abstract = {This paper introduces MedMCQA, a new large-scale, Multiple-Choice Question Answering (MCQA) dataset
  designed to address real-world medical entrance exam questions. 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 requires 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.}
}