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Data-driven approach of CUSUM algorithm in temporal aberrant event detection using interactive web applications

机译:使用交互式Web应用程序进行时态异常事件检测的CUSUM算法的数据驱动方法

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摘要

OBJECTIVE: In 2014/2015, Public Health Ontario developed disease-specific, cumulative sum (CUSUM)-based statistical algorithms for detecting aberrant increases in reportable infectious disease incidence in Ontario. The objective of this study was to determine whether the prospective application of these CUSUM algorithms, based on historical patterns, have improved specificity and sensitivity compared to the currently used Early Aberration Reporting System (EARS) algorithm, developed by the US Centers for Disease Control and Prevention.
机译:目的:2014/2015年,安大略省公共卫生局开发了基于疾病的累积总和(CUSUM)的统计算法,以检测安大略省可报告的传染病发病率异常增加。这项研究的目的是确定基于历史模式的这些CUSUM算法的预期应用是否与美国疾病控制和预防中心(US Centers for Disease Control and Center)开发的当前使用的早期畸变报告系统(EARS)算法相比具有更高的特异性和敏感性。预防。

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