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    System and method for improving clinical decisions by aggregating, validating and analysing genetic and phenotypic data
    1.
    发明授权
    System and method for improving clinical decisions by aggregating, validating and analysing genetic and phenotypic data 有权
    通过聚合，验证和分析遗传和表型数据来改进临床决策的系统和方法

    公开(公告)号：US08024128B2

    公开(公告)日：2011-09-20

    申请号：US11004274

    申请日：2004-12-03

    申请人： Matthew Rabinowitz ,  Wayne Chambliss ,  John Croswell ,  Miro Sarbaev ,  Milena Banjevic

    发明人： Matthew Rabinowitz ,  Wayne Chambliss ,  John Croswell ,  Miro Sarbaev ,  Milena Banjevic

    IPC分类号： G01N33/50

    CPC分类号： G06F19/24 ,  G06F19/18

    摘要： The information management system disclosed enables caregivers to make better decisions by using aggregated data. The system enables the integration, validation and analysis of genetic, phenotypic and clinical data from multiple subjects. A standardized data model stores a range of patient data in standardized data classes comprising patient profile, genetic, symptomatic, treatment and diagnostic information. Data is converted into standardized data classes using a data parser specifically tailored to the source system. Relationships exist between standardized data classes, based on expert rules and statistical models, and are used to validate new data and predict phenotypic outcomes. The prediction may comprise a clinical outcome in response to a proposed intervention. The statistical models and methods for training those models may be input according to a standardized template. Methods are described for selecting, creating and training the statistical models to operate on genetic, phenotypic, clinical and undetermined data sets.

    摘要翻译： 公开的信息管理系统使护理人员能够通过使用聚合数据做出更好的决策。 该系统能够整合，验证和分析来自多个受试者的遗传，表型和临床数据。 标准化数据模型将患者数据范围存储在包括患者概况，遗传，症状，治疗和诊断信息的标准化数据类别中。 使用专门针对源系统定制的数据解析器将数据转换为标准化数据类。 基于专家规则和统计模型，标准化数据类之间存在关系，用于验证新数据并预测表型结果。 预测可以包括响应于所提出的干预的临床结果。 可以根据标准化模板输入训练这些模型的统计模型和方法。 描述了用于选择，创建和训练统计模型以操作遗传，表型，临床和未确定数据集的方法。

    System and method for improving clinical decisions by aggregating, validating and analysing genetic and phenotypic data
    2.
    发明申请
    System and method for improving clinical decisions by aggregating, validating and analysing genetic and phenotypic data 有权
    通过聚合，验证和分析遗传和表型数据来改进临床决策的系统和方法

    公开(公告)号：US20060052945A1

    公开(公告)日：2006-03-09

    申请号：US11004274

    申请日：2004-12-03

    申请人： Matthew Rabinowitz ,  Wayne Chambliss ,  John Croswell ,  Miro Sarbaev ,  Milena Banjevic

    发明人： Matthew Rabinowitz ,  Wayne Chambliss ,  John Croswell ,  Miro Sarbaev ,  Milena Banjevic

    IPC分类号： G06F19/00

    CPC分类号： G06F19/24 ,  G06F19/18

    摘要： The information management system disclosed enables caregivers to make better decisions, faster, using aggregated genetic and phenotypic data. The system enables the integration, validation and analysis of genetic, phenotypic and clinical data from multiple subjects who may be at distributed facilities. A standardized data model stores a range of patient data in standardized data classes that encompass patient profile information, patient symptomatic information, patient treatment information, and patient diagnostic information including genetic information. Data from other systems is converted into the format of the standardized data classes using a data parser, or cartridge, specifically tailored to the source system. Relationships exist between standardized data classes that are based on expert rules and statistical models. The relationships are used both to validate new data, and to predict phenotypic outcomes based on available data. The prediction may relate to a clinical outcome in response to a proposed intervention by a caregiver. The statistical models may be inhaled into the system from electronic publications that define statistical models and methods for training those models, according to a standardized template. Methods are described for selecting, creating and training the statistical models to operate on genetic, phenotypic and clinical data, in particular for underdetermined data sets that are typical of genetic information. The disclosure also describes how security of the data is maintained by means of a robust security architecture, and robust user authentication such as biometric authentication, combined with application-level and data-level access privileges.

    摘要翻译： 所公开的信息管理系统使护理者能够使用聚合的遗传和表型数据更快地做出更好的决策。 该系统能够对可能在分布式设施的多个受试者进行遗传，表型和临床数据的整合，验证和分析。 标准化数据模型将一系列患者数据存储在包括患者资料信息，患者症状信息，患者治疗信息和包括遗传信息的患者诊断信息的标准化数据类别中。 使用专门针对源系统定制的数据解析器或磁带将来自其他系统的数据转换为标准化数据类的格式。 基于专家规则和统计模型的标准化数据类之间存在关系。 这些关系用于验证新数据，并根据可用数据预测表型结果。 该预测可能涉及到由照顾者提出的干预的临床结果。 根据标准化模板，统计模型可以从定义用于训练这些模型的统计模型和方法的电子出版物吸入系统。 描述了用于选择，创建和训练统计模型以操作遗传，表型和临床数据的方法，特别是对于遗传信息典型的未确定的数据集。 本公开还描述了如何通过鲁棒的安全架构以及健壮的用户认证（例如生物认证，以及应用级和数据级访问特权）来维护数据的安全性。