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METHOD AND APPARATUS FOR MULTI-DOMAIN ANOMALY PATTERN DEFINITION AND DETECTION

机译:用于多域异常模式的确定和检测的方法和装置

摘要

Disclosed herein is a multi-domain anomaly pattern definition and detection module. The module receives raw data from different kinds of anomalies from a variety of detection algorithms and generates scores associated with the data. If any scores exceed a threshold, the algorithm gathers further information such as counts or listings of detailed data for a geographic region. The detailed data can include emergency department and lab department data related to a particular health concern such as a respiratory syndrome. Summaries can identify anomalies and numbers of events according to geographic region and utilizing probability algorithms. Other databases such as animal data collected under the Department of Agriculture may also be utilized. The data is presented in a familiar form such as a map or a table such that a subject matter expert may determine whether to further investigate an anomaly as a potential risk, for example, a health risk.
机译:本文公开了一种多域异常模式定义和检测模块。该模块从各种检测算法接收来自不同种类异常的原始数据,并生成与数据相关的分数。如果任何分数超过阈值,该算法将收集更多信息,例如某个地理区域的详细数据的计数或列表。详细数据可以包括与特定健康问题(如呼吸综合征)有关的急诊科和实验室科数据。摘要可以根据地理区域并利用概率算法来识别异常和事件数量。也可以使用其他数据库,例如农业部下收集的动物数据。数据以熟悉的形式显示,例如地图或表格,以便主题专家可以确定是否进一步调查异常,以作为潜在风险(例如健康风险)。

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