Improving intensive care unit effectiveness and efficiency through improved data processing and analysis techniques.

该项目的目的是利用天体物理学领域大型数据集的广泛数据存档，搜索和分析技术，并将其应用于医院重症监护室（ICU）环境。特别是在过去的10年里，人们一直在大力推动确保复杂的、多波长的、多源的天体物理数据集采用兼容的格式，使天文学家能够探索来自世界各地的资源，查找数据，存储和共享文件，查询数据库，绘制和操作表格，交叉匹配目录，以及构建和运行脚本以自动执行任务序列。这些技术用于航天器数据集的基础上MSSL。这与粒子物理世界的类似推动一起，导致STFC资助的研究在处理大型复杂数据集方面拥有核心专业知识，这是我们今天许多（天文学）科学研究的基础。一个例子是Hinode航天器数据。在这种情况下，用户可以探测存档，搜索不同参数（如强度，速度，湍流）的变化，并以多种格式（如电影格式和光曲线）查看数据。该系统设计灵活，使用世界上任何人都可以探测的标准格式。我们有技术来寻找太阳大爆炸的触发因素，这涉及到导致灾难性后果的渐进变化。类似的技术可以用于采集患者数据并跟踪重症监护室（ICU）环境中患者状况的趋势（例如，心率、血压、血氧、电解质紊乱等）。目前，大多数数据集都是以不连续的方式采集的，在许多情况下，仍然以30分钟的间隔手工记录。这些数据目前没有储存，不能用于确定前兆。最长时间数据将在监测器中保存24小时，并在循环缓冲区中保存，以30分钟为间隔收集不连续数据，以便进行更长期的研究。这项研究的最终目标是提供一个软件工具，允许在生理学发生灾难性变化之前而不是之后做出反应，就像目前的情况一样。

The purpose of this project is to make use of the extensive data archiving, searching and analysis techniques for large datasets in the field of astrophysics and apply them to the hospital Intensive Care Unit (ICU) setting. Over the past 10 years in particular there has been a big push to ensure that complex, multi-wavelength, multi-source astrophysics datasets are in a compatible formats to enable astronomers to explore and resources from around the world, find data, store and share files, query databases, plot and manipulate tables, cross-match catalogues, and build and run scripts to automate sequences of tasks. These techniques are used for spacecraft datasets based at MSSL. This alongside with a similar push from the particle physics world has lead to a core expertise within STFC funded research in dealing with large and complex datasets that is the foundation of much of our (astronomy) scientific research today. One example is the Hinode spacecraft data. In this case a user can probe the archive searching for changes in different parameters such as intensity, velocity, turbulence, and view the data in multiple formats such as movie format and lightcurves. The system was designed to be flexible, using standard formats that can be probed by anyone in the world. We have techniques to look for triggers to large explosions on the Sun, which involve gradual changes that lead to a catastrophic outcome. Similar techniques could be used to acquire patient data and track trends in a patient's condition in an intensive care unit (ICU) setting (e.g. heart rate, blood pressure, blood oxygenation, electrolyte disturbances etc.). Currently most of the datasets are taken in a discontinuous way and in many cases are still recorded by hand at 30 minute intervals. The data is not currently stored and cannot be used to determine precursors. The longest period data will be kept in monitors will be on circular buffers for 24 hours with discontinuous data being collected on 30 min intervals to allow longer term study. The ultimate goal of this study is to provide a software tool that will allow a response BEFORE a catastrophic change happens physiologically rather than after, as is currently the case.