[AVI 2020] UTA4: Datasets

Several <em>datasets</em> are fostering innovation in higher-level functions for everyone, everywhere. By providing this repository, we hope to encourage the research community to focus on hard problems. In this project, we present <em>usability</em> (SUS), <em>workload</em> (NASA-TLX), <em>time</em> and <em>rates</em> (BIRADS) results of clinicians from our User Tests and Analysis 4 (UTA4) study. We also provide the <em>medical imaging DICOM files</em>. That said, we created UTA4: SUS Dataset, UTA4: NASA-TLX Dataset, UTA4: Time Dataset, UTA4: Rates Dataset and UTA4: Medical Imaging DICOM Files Dataset pages to provide further information regarding these <em>datasets</em> and respective repositories. Please follow this last information. The present data is a mirror of the <code>uta4-sm-vs-mm-sheets-nameless</code> repository. Work and results are published on a top Human-Computer Interaction (HCI) conference named AVI 2020 (page).多组数据集（datasets）正推动全球各地所有群体在高阶功能领域的创新实践。通过公开本仓库，我们期望鼓励研究社群聚焦于极具挑战性的核心问题。在本项目中，我们公开了来自用户测试与分析4（UTA4）研究中临床医师的系统可用性评分（System Usability Scale，SUS）、任务负荷量表（NASA-TLX）、耗时情况以及基于乳腺影像报告与数据系统（BIRADS）的评分结果，同时还提供了医学影像DICOM文件。为此，我们专门搭建了UTA4：系统可用性评分数据集、UTA4：任务负荷量表数据集、UTA4：耗时数据集、UTA4：BIRADS评分数据集以及UTA4：医学影像DICOM文件数据集等专属页面，以详细介绍上述数据集及其对应仓库的相关信息，请参考以上说明。本数据集为`uta4-sm-vs-mm-sheets-nameless`仓库的镜像版本。相关研究工作与成果已发表于顶级人机交互（Human-Computer Interaction，HCI）学术会议AVI 2020（会议页面）。