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Aiding infection analysis and diagnosis through temporally-contextualized matrix representations

机译:通过时间内容化矩阵表示辅导感染分析和诊断

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Determining infections and sepsis of severely burned adults in a timely fashion allows clinicians to provide necessary treatments to critically ill patients, potentially reducing the chance of mortality. In current practice, clinicians examine large amounts of heterogeneous medical records using a spreadsheet-like representation and perform analysis of descriptive statistics to aid in their decision making for sepsis diagnosis. A more efficient approach is required to streamline such a process; accordingly, we developed an interactive visual interface for supporting quick inspection and comparison of patients' retrospective clinical trajectories. In particular, we employ a timeline representation to present entire treatment contexts for individual patients, and an aggregated matrix representation for summarizing multiple data variables of individual patients over time. This provides clinicians with a compact and intuitive way to discover the important trends, patterns, and events that occur in the context of multiple patients. We present several possible use cases identified by clinicians using our system and show that our preliminary results have the potential to greatly improve diagnostic timing and accuracy of sepsis identification in critically ill patients.
机译:以及时的方式确定严重烧伤的成年人的感染和脓毒症允许临床医生为危重病人提供必要的治疗,可能降低死亡率的机会。在目前的实践中,临床医生使用类似电子表格的表示来检查大量的异质医疗记录,并对描述性统计数据进行分析,以帮助他们对脓毒症诊断的决策。简化这样的过程需要更有效的方法;因此,我们开发了一种交互式视觉界面,用于支持快速检查和患者回顾性临床轨迹的比较。特别是,我们采用时间表表示为个体患者提供整个治疗背景,以及用于总结多个患者的多个数据变量的聚合矩阵表示随着时间的推移。这为临床医生提供一个紧凑和直观的方式来发现的重要趋势,模式,以及发生在多个病人的背景事件。我们使用我们的系统展示了临床医生确定的几种可能用例,并表明我们的初步结果具有大大提高患者患者患者脓毒症鉴定的诊断时间和准确性。

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