Prediction of future adverse health events using neural networks by pre-processing input sequences to include presence features
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United States of America
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Apr 12, 2022
Grant Date -
May 14, 2020
app pub date -
Nov 13, 2019
filing date -
Nov 13, 2019
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Abstract
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.
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