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    SUPPORT VECTOR MACHINE-BASED METHOD FOR ANALYSIS OF SPECTRAL DATA
    3.
    发明申请
    SUPPORT VECTOR MACHINE-BASED METHOD FOR ANALYSIS OF SPECTRAL DATA 审中-公开
    支持向量机分析光谱数据分析方法

    公开(公告)号：US20140032451A1

    公开(公告)日：2014-01-30

    申请号：US13914607

    申请日：2013-06-10

    申请人： Health Discovery Corporation

    发明人： Asa Ben-Hur ,  Andre Elisseeff ,  Olivier Chappelle ,  Jason Weston

    IPC分类号： G06N99/00

    CPC分类号： G06N20/00 ,  G06K9/6215 ,  G06K9/6248 ,  G06K9/6269 ,  G06N20/10

    摘要： Support vector machines are used to classify data contained within a structured dataset such as a plurality of signals generated by a spectral analyzer. The signals are pre-processed to ensure alignment of peaks across the spectra. Similarity measures are constructed to provide a basis for comparison of pairs of samples of the signal. A support vector machine is trained to discriminate between different classes of the samples. to identify the most predictive features within the spectra. In a preferred embodiment feature selection is performed to reduce the number of features that must be considered.

    摘要翻译： 支持向量机用于对包含在结构化数据集中的数据进行分类，例如由频谱分析仪产生的多个信号。 信号被预处理，以确保谱峰的峰对准。 构建相似性度量以提供用于比较信号样本对的基础。 训练支持向量机以区分不同类别的样本。 以识别光谱中最具预测性的特征。 在优选实施例中，执行特征选择以减少必须考虑的特征的数量。

    COMPUTER-ASSISTED KARYOTYPING
    4.
    发明申请
    COMPUTER-ASSISTED KARYOTYPING 有权
    计算机辅助制作

    公开(公告)号：US20140016843A1

    公开(公告)日：2014-01-16

    申请号：US13922184

    申请日：2013-06-19

    申请人： HEALTH DISCOVERY CORPORATION

    发明人： Hong Zhang ,  Maher Albitar

    IPC分类号： G06K9/00

    CPC分类号： G06K9/00147 ,  G06K9/00127 ,  G06K9/0014

    摘要： A system and method for computer-assisted karyotyping includes a processor which receives a digitized image of metaphase chromosomes for processing in an image processing module and a classifier module. The image processing module may include a segmenting function for extracting individual chromosome images, a bend correcting function for straightening images of chromosomes that are bent or curved and a feature selection function for distinguishing between chromosome bands. The classifier module, which may be one or more trained kernel-based learning machines, receives the processed image and generates a classification of the image as normal or abnormal.

    摘要翻译： 用于计算机辅助核型分析的系统和方法包括接收中间染色体的数字化图像以在图像处理模块和分类器模块中进行处理的处理器。 图像处理模块可以包括用于提取单个染色体图像的分割功能，用于校正弯曲或弯曲的染色体的图像的弯曲校正功能和用于区分染色体带的特征选择功能。 可以是一个或多个训练有素的基于内核的学习机器的分类器模块接收经处理的图像，并且生成正常或异常的图像分类。

    Computer-assisted karyotyping
    5.
    发明授权
    Computer-assisted karyotyping 有权
    计算机辅助核型分析

    公开(公告)号：US09336430B2

    公开(公告)日：2016-05-10

    申请号：US13922184

    申请日：2013-06-19

    申请人： HEALTH DISCOVERY CORPORATION

    发明人： Hong Zhang ,  Maher Albitar

    IPC分类号： G06K9/00

    CPC分类号： G06K9/00147 ,  G06K9/00127 ,  G06K9/0014

    摘要： A system and method for computer-assisted karyotyping includes a processor which receives a digitized image of metaphase chromosomes for processing in an image processing module and a classifier module. The image processing module may include a segmenting function for extracting individual chromosome images, a bend correcting function for straightening images of chromosomes that are bent or curved and a feature selection function for distinguishing between chromosome bands. The classifier module, which may be one or more trained kernel-based learning machines, receives the processed image and generates a classification of the image as normal or abnormal.

    摘要翻译： 用于计算机辅助核型分析的系统和方法包括接收中间染色体的数字化图像以在图像处理模块和分类器模块中进行处理的处理器。 图像处理模块可以包括用于提取单个染色体图像的分割功能，用于校正弯曲或弯曲的染色体的图像的弯曲校正功能和用于区分染色体带的特征选择功能。 可以是一个或多个训练有素的基于内核的学习机器的分类器模块接收经处理的图像，并且生成正常或异常的图像分类。

    IDENTIFICATION OF PATTERN SIMILARITIES BY UNSUPERVISED CLUSTER ANALYSIS
    6.
    发明申请
    IDENTIFICATION OF PATTERN SIMILARITIES BY UNSUPERVISED CLUSTER ANALYSIS 审中-公开
    通过不一致的聚类分析识别图案类型

    公开(公告)号：US20130297607A1

    公开(公告)日：2013-11-07

    申请号：US13934166

    申请日：2013-07-02

    申请人： Health Discovery Corporation

    发明人： Asa Ben-Hur ,  Andre Elisseeff ,  Isabelle Guyon

    IPC分类号： G06F17/30

    CPC分类号： G06F16/35 ,  G06K9/6218 ,  G16B25/00 ,  G16B40/00

    摘要： A method is provided for unsupervised clustering of data to identify pattern similarities. A clustering algorithm randomly divides the data into k different subsets and measures the similarity between pairs of datapoints within the subsets, assigning a score to the pairs based on similarity, with the greatest similarity giving the highest correlation score. A distribution of the scores is plotted for each k. The highest value of k that has a distribution that remains concentrated near the highest correlation score corresponds to the number of classes having pattern similarities.

    摘要翻译： 提供了一种用于无监督的数据聚类以识别图案相似性的方法。 聚类算法将数据随机分为k个不同的子集，并测量子集内的数据点对之间的相似度，并根据相似度为该对分配一个分数，最大相似度给出最高相关分数。 为每个k绘制得分的分布。 具有在最高相关分数附近集中的分布的k的最高值对应于具有模式相似性的类的数量。