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

Ankit Pal, Logesh Kumar Umapathi, Malaikannan Sankarasubbu
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引用次数: 70

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.
MedMCQA:用于医学领域问答的大规模多主题多选择数据集
本文介绍了MedMCQA,一个新的大规模选择题答案(MCQA)数据集,旨在解决现实世界的医学入学考试问题。收集了超过194,000个高质量的AIIMS \&NEET PG入学考试mcq,涵盖24,000个医疗保健主题和21个医学科目,平均令牌长度为12.77,主题多样性高。每个样本包含一个问题、正确答案和其他选项,这些选项需要更深入的语言理解,因为它测试了模型在广泛的医学科目和主题上的10+推理能力。本研究提供了解决方案的详细解释以及上述信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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