Patent ID: 9652712
Date: 2017-05-16
CPC Classifications: G06N,G16H

Claim:
1. A method comprising: obtaining a plurality of initial temporal sequences of health events, processing each of the plurality of initial temporal sequences of health events using a recurrent neural network to generate, for each of the initial temporal sequences, a respective network internal state of the recurrent neural network for each time step in the initial temporal sequence, storing, for each of the plurality of initial temporal sequences, one or more of the network internal states for the time steps in the temporal sequence in an internal state repository; obtaining a first temporal sequence of health events that is associated with a current patient; processing the first temporal sequence of health events using the recurrent neural network to generate a sequence internal state for the first temporal sequence; and comparing the sequence internal state for the first temporal sequence to the network internal states for the initial temporal sequences that are stored in the internal state repository to determine a plurality of network internal states from the network internal states for the initial temporal sequences that are similar to the sequence internal state; selecting, as temporal sequences that are likely to include health events that are predictive of future health events that may become associated with the current patient, the initial temporal sequences corresponding to the similar network internal states.