论文标题
使用Jensen-Shannon Divergence在ICU患者中对ICU患者中败血症的在线关键状态检测
Online Critical-State Detection of Sepsis Among ICU Patients using Jensen-Shannon Divergence
论文作者
论文摘要
败血症是由宿主对感染的失调反应引起的严重医疗状况，其发病率和死亡率很高。即使以如此高级的发生率，败血症的检测和诊断仍在挑战。至关重要的是要准确预测败血症的发作，同时还可以识别以可解释方式促进这一预测的特定生理异常。这项研究提出了一种新的方法，可以使用非参数概率分布估计值定量测量患者与参考组之间的差异，并强调使用基于Jensen Shannon Divergence的单个样本分析方法出现异常时。我们表明，我们可以定量区分这两组，并实时衡量差异，同时确定有助于患者预后的特定生理因素。我们展示了我们在佐治亚州格雷迪医院亚特兰大录取的患者的现实数据集上的方法。
Sepsis is a severe medical condition caused by a dysregulated host response to infection that has a high incidence and mortality rate. Even with such a high-level occurrence rate, the detection and diagnosis of sepsis continues to pose a challenge. There is a crucial need to accurately forecast the onset of sepsis promptly while also identifying the specific physiologic anomalies that contribute to this prediction in an interpretable fashion. This study proposes a novel approach to quantitatively measure the difference between patients and a reference group using non-parametric probability distribution estimates and highlight when abnormalities emerge using a Jensen-Shannon divergence-based single sample analysis approach. We show that we can quantitatively distinguish between these two groups and offer a measurement of divergence in real time while simultaneously identifying specific physiologic factors contributing to patient outcomes. We demonstrate our approach on a real-world dataset of patients admitted to Atlanta, Georgia's Grady Hospital.
