Annotated Question-Answer Pairs for Clinical Notes in the MIMIC-III Database

Clinical question answering (QA) (or reading comprehension) aims to automatically answer questions from medical professionals based on clinical texts. We release this dataset, which contains 1287 annotated QA pairs on 36 sampled discharge summaries from MIMIC-III Clinical Notes, to facilitate the clinical question answering task. Questions in our dataset are either verified or directly generated by clinical experts.

Note that the primary purpose of this dataset is to test the generalizability of a QA model, i.e., whether a QA model that is trained on other datasets can answer questions on this dataset (which may have a different distribution compared with the training data), rather than to train a QA model. Hence the scale of our annotations is relatively small compared to some existing QA datasets.

临床问答（QA）或阅读理解旨在根据临床文本自动回答医疗专业人士提出的问题。本数据集包含从MIMIC-III临床笔记中选取的36篇样本出院小结上的1287个标注问答对，旨在促进临床问答任务的实现。数据集中的问题要么经临床专家验证，要么直接由其生成。值得注意的是，本数据集的主要目的是测试问答模型的可推广性，即一个在其它数据集上训练的问答模型能否回答本数据集上的问题（与训练数据相比，本数据集可能具有不同的分布），而非用于训练问答模型。因此，相较于一些现有的问答数据集，本数据集的标注规模相对较小。