MedQA 医学文本问答数据集

MedQA 数据集是一个面向医学领域的问答数据集，模拟了美国医疗执照考试 (USMLE) 的风格，由麻省理工大学和华中科技大学的研究团队于 2020 年发布，相关论文成果为「What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams」。该数据集从专业医学考试中收集，涵盖英语、简体中文和繁体中文，分别包含 12,723 、 34,251 和 14,123 个问题，旨在评估模型对医学知识的理解和应用能力。。

MedQA is a medical-domain question answering dataset modeled after the United States Medical Licensing Examination (USMLE). It was released in 2020 by a research team from the Massachusetts Institute of Technology and Huazhong University of Science and Technology, with its associated paper titled "What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams". This dataset is collected from professional medical examinations, covering English, Simplified Chinese and Traditional Chinese versions, which respectively contain 12,723, 34,251 and 14,123 questions. It aims to evaluate models' ability to understand and apply medical knowledge.

搜集汇总

背景与挑战

背景概述

MedQA数据集是一个面向医学领域的问答数据集，模拟美国医疗执照考试（USMLE）风格，由麻省理工大学和华中科技大学团队于2020年发布，涵盖英语、简体中文和繁体中文，分别包含12,723、34,251和14,123个问题。该数据集基于专业医学考试构建，确保问题高质量和专业性，并附带医学教科书语料库，支持模型训练和评估，旨在测试模型对医学知识的理解和应用能力。