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

Source: [MedMCQA : A Large-scale Multi-Subject Multi-Choice Dataset for Medical domain Question Answering](<https://www.sota2.com/research/paper/68fa6c1c1e209131cea32442>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-12-14T18:21:38.522Z

Authors: Ankit Pal, Logesh Kumar Umapathi, Malaikannan Sankarasubbu

Published: 2022-03-27T18:59:16.000Z

## 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.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2203.14371>)

[PDF](<https://arxiv.org/pdf/2203.14371.pdf>)

[Implementation](<http://medmcqa.github.io/>)