Annu Int Conf IEEE Eng Med Biol Soc. 2022 Jul;2022:2286-2289. doi: 10.1109/EMBC48229.2022.9871973.
Sepsis is one of the most frequent causes of death in Intensive Care Units, and its prognosis greatly depend on timeliness of diagnosis. MIMIC-III database is a frequent source of data for developing method for automatic sepsis detection. However, the heterogeneity of data jeopardize the feasibility of the task. In this work we propose a selection strategy for generating high quality data suitable for training a sepsis detection system based on the utilization of only plethysmographic data. Clinical relevance A system for detecting sepsis based only on PPG may be potentially at virtually no cost in any case clinicians suspect the possibility of developing sepsis.
脓毒症是重症监护病房中最常见的死亡原因之一,其预后在很大程度上取决于诊断的及时性。MIMIC-III 数据库是开发自动脓毒症检测方法的常用数据源。然而,数据的异质性危及了该任务的可行性。在这项工作中,我们提出了一种选择策略,用于生成高质量的数据,这些数据适合基于仅容积描记数据的脓毒症检测系统的训练。临床相关性 仅基于 PPG 检测脓毒症的系统在任何情况下都可能具有潜在的成本效益,只要临床医生怀疑有可能发生脓毒症。