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CONVOLUTIONAL NEURAL NETWORK SYSTEMS AND METHODS FOR DATA CLASSIFICATION

机译:卷积神经网络系统和数据分类方法

摘要

Classification of cancer condition, in a plurality of different cancer conditions, for a species, is provided in which, for each training subject in a plurality of training subjects, there is obtained a cancer condition and a genotypic data construct including genotypic information for the respective training subject. Genotypic constructs are formatted into corresponding vector sets comprising one or more vectors. Vector sets are provided to a network architecture including a convolutional neural network path comprising at least a first convolutional layer associated with a first filter that comprise a first set of filter weights and a scorer. Scores, corresponding to the input of vector sets into the network architecture, are obtained from the scorer. Comparison of respective scores to the corresponding cancer condition of the corresponding training subjects is used to adjust the filter weights thereby training the network architecture to classify cancer condition.
机译:提供针对物种的在多种不同癌症状况中的癌症状况的分类,其中,针对多个训练受试者中的每个训练受试者,获得癌症状况和包括各自基因型信息的基因型数据构建体培训主题。基因型构建体被格式化为包含一个或多个载体的相应载体集。将向量集提供给包括卷积神经网络路径的网络体系结构,该卷积神经网络路径包括至少一个与第一滤波器相关联的第一卷积层,该第一卷积层包括第一组滤波器权重和计分器。从得分器获得与向量集输入到网络体系结构相对应的得分。将各个得分与相应训练对象的相应癌症状况的比较用于调整过滤器权重,从而训练网络架构以对癌症状况进行分类。

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