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    Versatile Data Model
    1.
    发明申请
    Versatile Data Model 审中-公开
    多功能数据模型

    公开(公告)号：US20160063043A1

    公开(公告)日：2016-03-03

    申请号：US14472932

    申请日：2014-08-29

    申请人： Accenture Global Services Limited

    发明人： Dennis Carroll ,  Cecil Lynch ,  German Acuna ,  Anh-Hoang Vo ,  Thomas D. Perry

    IPC分类号： G06F17/30

    CPC分类号： G06F16/2246 ,  G06F16/212 ,  G06F16/25 ,  G06F16/282

    摘要： Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for processing a data model, a data file and user input to provide a populated data model, the populated data model including: a data content table having one or more navigation columns and one or more content columns, at least one navigation column including one or more key values of a key node, and at least one content column including data values of a plurality of data values, and a foreign key table having one or more navigation columns and one or more relationship columns, at least one navigation column including one or more key values of a foreign key node, and the one or more relationship columns associating at least one key node of the data content table to a respective foreign key node.

    摘要翻译： 方法，系统和装置，包括在计算机存储介质上编码的用于处理数据模型的计算机程序，数据文件和用户输入以提供填充的数据模型，所填充的数据模型包括：具有一个或多个 导航列和一个或多个内容列，包括关键节点的一个或多个键值的至少一个导航列，以及包括多个数据值的数据值的至少一个内容列，以及包含多个数据值的外键列 导航列和一个或多个关系列，包括外键节点的一个或多个键值的至少一个导航列，以及将数据内容表的至少一个关键节点与各个外键节点相关联的一个或多个关系列 。

    Predictive Model Generator
    2.
    发明申请
    Predictive Model Generator 审中-公开
    预测模型发生器

    公开(公告)号：US20160055412A1

    公开(公告)日：2016-02-25

    申请号：US14464330

    申请日：2014-08-20

    申请人： Accenture Global Services Limited

    发明人： Dennis Carroll ,  Cecil Lynch ,  German Acuna ,  Anh-Hoang Vo

    IPC分类号： G06N5/04 ,  G06F19/00

    CPC分类号： G06N5/04 ,  G16H50/20 ,  G16H50/30 ,  G16H50/70

    摘要： Methods, systems, and apparatuses, including computer programs encoded on a computer storage medium, can be implemented to perform actions including receiving input data defining a predictive model, the predictive model including multiple features. The actions further include weighting the predictive model iteratively for each feature, using actual data including values for each feature for multiple entities within a population, by iteratively adjusting a current weight for the feature by a momentum until the momentum equals zero, the momentum being iteratively adjusted by a momentum factor based on whether a model score improves, the model score being calculated based on the actual data. The actions further include calculating a value score for the entity using the weighted predictive model.

    摘要翻译： 可以实现包括在计算机存储介质上编码的计算机程序的方法，系统和装置，以执行包括接收定义预测模型的输入数据的动作，所述预测模型包括多个特征。 动作进一步包括通过使用动量等于零的动量迭代地调整特征的当前权重，使用实际数据包括群体内的多个实体的每个特征的值来迭代地对每个特征加权预测模型，该动量被迭代地 根据模型得分是否改善，通过动量因子进行调整，模型得分根据实际数据计算。 这些动作进一步包括使用加权预测模型计算实体的价值得分。

    SYSTEM FOR ANONYMIZING AND AGGREGATING PROTECTED HEALTH INFORMATION
    3.
    发明申请
    SYSTEM FOR ANONYMIZING AND AGGREGATING PROTECTED HEALTH INFORMATION 审中-公开
    免疫和聚集保护性健康信息系统

    公开(公告)号：US20150149208A1

    公开(公告)日：2015-05-28

    申请号：US14092168

    申请日：2013-11-27

    申请人： Accenture Global Services Limited

    发明人： Cecil O. Lynch ,  Dennis Carroll ,  Andrew J. Truscott

    IPC分类号： G06F19/00

    CPC分类号： G16H10/60 ,  G06F21/6254

    摘要： A patient anonymizing system includes a plurality of hashing appliances and data sources. Each appliance receives medical records containing at least confidential protected health information (PHI). A salt value is appended to each confidential PHI, and a hash is generated, which replaces the confidential PHI to generate an anonymized record. A master patient index server aggregates the anonymized records. A vector and cluster matching engine determines if the anonymized record matches a unique patient identifier corresponding to a second anonymized record. A comparison vector is generated by comparing hash values of the confidential PHI with hash values in the second anonymized record, and is crossed with a confidence vector having weights based on match conditions. This produces a match confidence level, which is compared to a threshold. If the threshold is met, the anonymized record is mapped to the unique patient identifier associated with the second record.

    摘要翻译： 患者匿名系统包括多个散列设备和数据源。 每个设备都收到至少包含机密保护健康信息（PHI）的医疗记录。 将一个盐值附加到每个机密PHI上，并产生一个哈希值，它代替机密PHI以生成一个匿名记录。 主病人索引服务器聚合匿名记录。 矢量和集群匹配引擎确定匿名记录是否匹配与第二匿名记录相对应的唯一患者识别符。 通过将秘密PHI的散列值与第二匿名记录中的散列值进行比较来生成比较矢量，并且与基于匹配条件的权重的置信向量相交。 这产生匹配置信水平，其与阈值进行比较。 如果阈值被满足，则匿名记录被映射到与第二记录相关联的唯一的患者识别符。

    System for anonymizing and aggregating protected health information
    5.
    发明授权
    System for anonymizing and aggregating protected health information 有权

    公开(公告)号：US10607726B2

    公开(公告)日：2020-03-31

    申请号：US14092168

    申请日：2013-11-27

    申请人： Accenture Global Services Limited

    发明人： Cecil O. Lynch ,  Dennis Carroll ,  Andrew J. Truscott

    IPC分类号： G16H10/60 ,  G06F21/62 ,  G06F19/00

    摘要： A patient anonymizing system includes a plurality of hashing appliances and data sources. Each appliance receives medical records containing at least confidential protected health information (PHI). A salt value is appended to each confidential PHI, and a hash is generated, which replaces the confidential PHI to generate an anonymized record. A master patient index server aggregates the anonymized records. A vector and cluster matching engine determines if the anonymized record matches a unique patient identifier corresponding to a second anonymized record. A comparison vector is generated by comparing hash values of the confidential PHI with hash values in the second anonymized record, and is crossed with a confidence vector having weights based on match conditions. This produces a match confidence level, which is compared to a threshold. If the threshold is met, the anonymized record is mapped to the unique patient identifier associated with the second record.