论文标题
MEDMCQA：一个大规模的多主体多选择数据集用于医疗领域问题答案
MedMCQA : A Large-scale Multi-Subject Multi-Choice Dataset for Medical domain Question Answering
论文作者
论文摘要
本文介绍了MEDMCQA，这是一种新的大规模，多项选择性答案（MCQA）数据集，旨在解决现实世界中的医学入学考试问题。超过194K高质量的AIIMS \＆NEET PG入学考试MCQ涵盖了2.4K医疗保健主题，并收集了21个医疗主题，平均令牌长度为12.77，高主题多样性。每个示例都包含一个问题，正确的答案以及其他选项，该选项需要更深入的语言理解，因为它可以在广泛的医学主题\＆主题中测试模型的10+推理能力。本研究提供了对解决方案的详细说明以及上述信息。
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.
