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

被引：0
|
作者：
Pal, Ankit [1 ]
Umapathi, Logesh Kumar [1 ]
Sankarasubbu, Malaikannan [1 ]
机构：
[1] Saama AI Res, Chennai, Tamil Nadu, India
来源：
CONFERENCE ON HEALTH, INFERENCE, AND LEARNING, VOL 174 | 2022年 / 174卷
关键词：
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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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页码：248 / 260
页数：13
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