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    METHODS FOR ANALYZING HIGH DIMENSIONAL DATA FOR CLASSIFYING, DIAGNOSING, PROGNOSTICATING, AND/OR PREDICTING DISEASES AND OTHER BIOLOGICAL STATES
    1.
    发明申请
    METHODS FOR ANALYZING HIGH DIMENSIONAL DATA FOR CLASSIFYING, DIAGNOSING, PROGNOSTICATING, AND/OR PREDICTING DISEASES AND OTHER BIOLOGICAL STATES 失效
    分析高分辨率数据进行分类，诊断，预处理和/或预测疾病及其他生物学状态的方法

    公开(公告)号：US20100312486A1

    公开(公告)日：2010-12-09

    申请号：US12858674

    申请日：2010-08-18

    申请人： Javed Khan ,  Markus Ringnér ,  Carsten Peterson ,  Paul Meltzer

    发明人： Javed Khan ,  Markus Ringnér ,  Carsten Peterson ,  Paul Meltzer

    IPC分类号： G06F19/00

    CPC分类号： G06F19/20 ,  C12Q1/6886 ,  G06F19/12 ,  G06F19/24

    摘要： A method of diagnosing, predicting, or prognosticating about a disease that includes obtaining experimental data, wherein the experimental data is high dimensional data, filtering the data, reducing the dimensionality of the data through use of one or more methods, training a supervised pattern recognition method, ranking individual data points from the data, wherein the ranking is dependent on the outcome of the supervised pattern recognition method, choosing multiple data points from the data, wherein the choice is based on the relative ranking of the individual data points, and using the multiple data points to determine if an unknown set of experimental data indicates a diseased condition, a predilection for a diseased condition, or a prognosis about a diseased condition.

    摘要翻译： 一种诊断，预测或预测疾病的方法，包括获得实验数据，其中实验数据是高维数据，过滤数据，通过使用一种或多种方法降低数据的维度，训练监督模式识别 方法，从数据中排列各个数据点，其中排序取决于监督模式识别方法的结果，从数据中选择多个数据点，其中所述选择基于各个数据点的相对排名，并且使用 多个数据点以确定未知的一组实验数据是否表示疾病状况，患病条件的偏好或关于患病状况的预后。

    Methods for analyzing high dimensional data for classifying, diagnosing, prognosticating, and/or predicting diseases and other biological states
    2.
    发明授权
    Methods for analyzing high dimensional data for classifying, diagnosing, prognosticating, and/or predicting diseases and other biological states 失效
    分析高维数据以分类，诊断，预测和/或预测疾病和其他生物状态的方法

    公开(公告)号：US08065092B2

    公开(公告)日：2011-11-22

    申请号：US12858674

    申请日：2010-08-18

    申请人： Javed Khan ,  Markus Ringnér ,  Carsten Peterson ,  Paul Meltzer

    发明人： Javed Khan ,  Markus Ringnér ,  Carsten Peterson ,  Paul Meltzer

    IPC分类号： G06F19/00 ,  G06F17/10 ,  G06N3/00 ,  G06G7/00 ,  G06G7/58

    CPC分类号： G06F19/20 ,  C12Q1/6886 ,  G06F19/12 ,  G06F19/24

    摘要： A method of diagnosing, predicting, or prognosticating about a disease that includes obtaining experimental data, wherein the experimental data is high dimensional data, filtering the data, reducing the dimensionality of the data through use of one or more methods, training a supervised pattern recognition method, ranking individual data points from the data, wherein the ranking is dependent on the outcome of the supervised pattern recognition method, choosing multiple data points from the data, wherein the choice is based on the relative ranking of the individual data points, and using the multiple data points to determine if an unknown set of experimental data indicates a diseased condition, a predilection for a diseased condition, or a prognosis about a diseased condition.

    摘要翻译： 一种诊断，预测或预测疾病的方法，包括获得实验数据，其中实验数据是高维数据，过滤数据，通过使用一种或多种方法降低数据的维度，训练监督模式识别 方法，从数据中排列各个数据点，其中排序取决于监督模式识别方法的结果，从数据中选择多个数据点，其中所述选择基于各个数据点的相对排名，并且使用 多个数据点以确定未知的一组实验数据是否表示疾病状况，患病条件的偏好或关于患病状况的预后。

    Methods for analyzing high dimensional data for classifying, diagnosing, prognosticating, and/or predicting diseases and other biological states
    5.
    发明授权
    Methods for analyzing high dimensional data for classifying, diagnosing, prognosticating, and/or predicting diseases and other biological states 有权
    分析高维数据以分类，诊断，预测和/或预测疾病和其他生物状态的方法

    公开(公告)号：US07783431B2

    公开(公告)日：2010-08-24

    申请号：US11928901

    申请日：2007-10-30

    申请人： Javed Khan ,  Markus Ringner ,  Carsten Peterson ,  Paul Meltzer

    发明人： Javed Khan ,  Markus Ringner ,  Carsten Peterson ,  Paul Meltzer

    IPC分类号： G06F19/00 ,  G06F17/10 ,  G06N3/00 ,  G06G7/00 ,  G06G7/58

    CPC分类号： G06F19/20 ,  C12Q1/6886 ,  G06F19/12 ,  G06F19/24

    摘要： A method of diagnosing, predicting, or prognosticating about a disease that includes obtaining experimental data, wherein the experimental data is high dimensional data, filtering the data, reducing the dimensionality of the data through use of one or more methods, training a supervised pattern recognition method, ranking individual data points from the data, wherein the ranking is dependent on the outcome of the supervised pattern recognition method, choosing multiple data points from the data, wherein the choice is based on the relative ranking of the individual data points, and using the multiple data points to determine if an unknown set of experimental data indicates a diseased condition, a predilection for a diseased condition, or a prognosis about a diseased condition.

    摘要翻译： 一种诊断，预测或预测疾病的方法，包括获得实验数据，其中实验数据是高维数据，过滤数据，通过使用一种或多种方法降低数据的维度，训练监督模式识别 方法，从数据中排列各个数据点，其中排序取决于监督模式识别方法的结果，从数据中选择多个数据点，其中所述选择基于各个数据点的相对排名，并且使用 多个数据点以确定未知的一组实验数据是否表示疾病状况，患病条件的偏好或关于患病状况的预后。

    Methods for Analyzing High Dimension Data for Classifying, Diagnosing, Prognosticating, and/or Predicting Diseases and Other Biological States
    7.
    发明申请
    Methods for Analyzing High Dimension Data for Classifying, Diagnosing, Prognosticating, and/or Predicting Diseases and Other Biological States 有权
    分析，诊断，预测和/或预测疾病和其他生物状态的高维数据的方法

    公开(公告)号：US20090035766A1

    公开(公告)日：2009-02-05

    申请号：US11928901

    申请日：2007-10-30

    申请人： Javed Khan ,  Markus Ringner ,  Carsten Peterson ,  Paul Meltzer

    发明人： Javed Khan ,  Markus Ringner ,  Carsten Peterson ,  Paul Meltzer

    IPC分类号： C12Q1/68 ,  A61B5/00

    CPC分类号： G06F19/20 ,  C12Q1/6886 ,  G06F19/12 ,  G06F19/24

    摘要： A method of diagnosing, predicting, or prognosticating about a disease that includes obtaining experimental data, wherein the experimental data is high dimensional data, filtering the data, reducing the dimensionality of the data through use of one or more methods, training a supervised pattern recognition method, ranking individual data points from the data, wherein the ranking is dependent on the outcome of the supervised pattern recognition method, choosing multiple data points from the data, wherein the choice is based on the relative ranking of the individual data points, and using the multiple data points to determine if an unknown set of experimental data indicates a diseased condition, a predilection for a diseased condition, or a prognosis about a diseased condition.

    摘要翻译： 一种诊断，预测或预测疾病的方法，包括获得实验数据，其中实验数据是高维数据，过滤数据，通过使用一种或多种方法降低数据的维度，训练监督模式识别 方法，从数据中排列各个数据点，其中排序取决于监督模式识别方法的结果，从数据中选择多个数据点，其中所述选择基于各个数据点的相对排名，并且使用 多个数据点以确定未知的一组实验数据是否表示疾病状况，患病条件的偏好或关于患病状况的预后。

    Sets of probes and primers for the diagnosis of select cancers
    8.
    发明授权
    Sets of probes and primers for the diagnosis of select cancers 失效
    用于诊断选择性癌症的探针和引物组

    公开(公告)号：US08263759B2

    公开(公告)日：2012-09-11

    申请号：US11981502

    申请日：2007-10-30

    申请人： Javed Khan ,  Markus Ringner ,  Carsten Peterson ,  Paul Meltzer

    发明人： Javed Khan ,  Markus Ringner ,  Carsten Peterson ,  Paul Meltzer

    IPC分类号： C07H21/02 ,  C07H21/04 ,  C12Q1/68

    CPC分类号： G06F19/24 ,  G06F19/20 ,  Y02A90/26

    摘要： A method of diagnosing a disease that includes obtaining experimental data on gene selections. The gene selection functions to characterize a cancer when the expression of that gene selection is compared to the identical selection from a noncancerous cell or a different type of cancer cell. The invention also includes a method of targeting at least one product of a gene that includes administration of a therapeutic agent. The invention also includes the use of a gene selection for diagnosing a cancer.

    摘要翻译： 一种诊断疾病的方法，包括获得关于基因选择的实验数据。 当将该基因选择的表达与来自非癌细胞或不同类型的癌细胞的相同选择进行比较时，基因选择用于表征癌症。 本发明还包括靶向至少一种包括施用治疗剂的基因产物的方法。 本发明还包括使用基因选择来诊断癌症。

    Method and device for automatic evaluation of cereal grains and other granular products
    10.
    发明授权
    Method and device for automatic evaluation of cereal grains and other granular products 失效
    自动评估谷物和其他颗粒产品的方法和装置

    公开(公告)号：US5956413A

    公开(公告)日：1999-09-21

    申请号：US997548

    申请日：1997-12-23

    申请人： Rickard Oste ,  Peter Egelberg ,  Carsten Peterson ,  Patrik Soderlund ,  Lennart Sjostedt

    发明人： Rickard Oste ,  Peter Egelberg ,  Carsten Peterson ,  Patrik Soderlund ,  Lennart Sjostedt

    IPC分类号： B07C5/342 ,  G06K9/00

    CPC分类号： B07C5/3425

    摘要： In automatic evaluation of cereal kernels or like granular products handled in bulk, the kernels are conveyed on a vibrating conveyor belt (15). Owing to the vibrations, the kernels are spread and settled in grooves (14) in the belt so as to be oriented in essentially the same direction. A video camera (40) produces digital images of all the kernels on the belt. The kernels are identified in the images, and for each kernel input signals are produced and then sent to a neural network based on picture element values for the picture elements representing each kernel. A neural network then determines which of a plurality of predetermined classes that each kernel belongs.

    摘要翻译： 在批量处理的谷物或类似颗粒产品的自动评估中，在振动输送带（15）上输送颗粒。 由于振动，将颗粒扩散并沉降在带中的凹槽（14）中，以便沿基本相同的方向定向。 摄像机（40）产生皮带上所有内核的数字图像。 在图像中识别内核，并且对于每个内核输入信号被产生，然后基于表示每个内核的图像元素的图像元素值发送到神经网络。 然后，神经网络确定每个内核所属的多个预定类别中的哪一个。