公开(公告)号：US20120136676A1

公开(公告)日：2012-05-31

申请号：US13306234

申请日：2011-11-29

申请人： Colin Goodall ,  Guy Jacobson ,  Greg B. Kinne ,  Arnold Lent

发明人： Colin Goodall ,  Guy Jacobson ,  Greg B. Kinne ,  Arnold Lent

IPC分类号： G06Q50/22

CPC分类号： G06Q10/063 ,  G06Q10/0635 ,  G06Q50/22 ,  Y02A90/22 ,  Y02A90/26

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.

摘要翻译： 这里公开了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，则算法收集更多信息，例如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相关的急诊部门和实验室部门数据，如呼吸综合征。 总结可以根据地理区域和利用概率算法识别事件的异常和数量。 还可以利用其他数据库，如农业部收集的动物数据。 数据以熟悉的形式呈现，例如地图或表格，使得主题专家可以确定是否进一步调查异常作为潜在风险，例如健康风险。

公开(公告)号：US08090592B1

公开(公告)日：2012-01-03

申请号：US11931789

申请日：2007-10-31

申请人： Colin Goodall ,  Guy Jacobson ,  Greg B. Kinne ,  Arnold Lent

发明人： Colin Goodall ,  Guy Jacobson ,  Greg B. Kinne ,  Arnold Lent

IPC分类号： G06Q50/00

CPC分类号： G06Q10/063 ,  G06Q10/0635 ,  G06Q50/22 ,  Y02A90/22

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 one or more scores exceed a threshold, then the algorithm gathers further information which may include counts or listings of detailed data for a geographic region which may include such information as emergency department and lab department data related to a particular health concern such as a respiratory syndrome. Summaries are provided which may 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.

摘要翻译： 这里公开了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。 如果一个或多个分数超过阈值，则该算法收集进一步的信息，其可以包括地理区域的详细数据的计数或列表，所述地理区域可以包括诸如与特定健康问题相关的紧急部门和实验室部门数据的信息，例如呼吸 综合征 提供摘要，可以根据地理区域和利用概率算法识别事件的异常和数量。 还可以利用其他数据库，如农业部收集的动物数据。 数据以熟悉的形式呈现，例如地图或表格，使得主题专家可以确定是否进一步调查异常作为潜在风险，例如健康风险。