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

A large-scale MCQA dataset addressing real-world medical entrance exam questions is introduced, testing models across various medical subjects and reasoning abilities.

Year
2022
Venue
arXiv 2022
Authors
3
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arxiv.org/abs/2203.14371ARXIV-DEFAULT
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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.

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3