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PREDICTION OF FUTURE ADVERSE HEALTH EVENTS USING NEURAL NETWORKS BY PRE-PROCESSING INPUT SEQUENCES TO INCLUDE PRESENCE FEATURES

机译:通过预处理输入序列来预测使用神经网络的未来不良健康事件以包括存在功能

摘要

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting future adverse health events using neural networks. One of the methods includes receiving electronic health record data for a patient; generating, from the electronic health record data, an input sequence comprising a respective feature representation at each of a plurality of time window time steps, comprising, for each time window time step: determining, for each of the possible numerical features, whether the numerical feature occurred during the time window; and generating, for each of the possible numerical features, one or more presence features that identify whether the numerical feature occurred during the time window; and processing the input sequence using a neural network to generate a neural network output that characterizes a predicted likelihood that an adverse health event will occur to the patient.
机译:方法,系统和设备,包括在计算机存储介质上编码的计算机程序,用于使用神经网络预测未来的不利健康事件。 其中一种方法包括接收患者的电子健康记录数据; 从电子健康记录数据生成一个输入序列,该输入序列包括在多个时间窗口时间步骤中的每一个处的相应特征表示,包括为每个时间窗口时间步骤:确定每个可能的数字特征,无论是数值吗? 特征在时间窗口中发生; 对于每个可能的数值特征,一个或多个存在特征,可以识别在时间窗口期间是否发生的一个或多个存在功能; 使用神经网络处理输入序列以产生特征的神经网络输出,其表征患者将发生不利健康事件的预测可能性。

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