A recurrent neural network system for predicting a likelihood of occurrence of a heart attack or stroke, the recurrent neural network system being configured to process a temporal sequence comprising a respective input at each of a plurality of time steps, the recurrent neural network system comprising: one or more recurrent neural network layers and one or more logistic regression nodes, said layers and nodes trained on the same set of labeled training sequences; wherein the one or more recurrent neural network layers are configured to, for each of the plurality of time steps: receive the input at the time step; and collectively process the input at the time step to generate a network internal state for the time step; wherein each of the logistic regression nodes corresponds to a respective condition from a predetermined set of conditions, and wherein each of the logistic regression nodes is configured to, for each of the plurality of time steps: receive the network internal state for the time step; and process the network internal state for the time step in accordance with current values of a set of parameters of the logistic regression node to generate a future condition score for the corresponding condition for the time step, wherein the future condition score for the corresponding condition represents a likelihood that the corresponding condition will be satisfied within a specified time period of the input at the time step, wherein the inputs at the plurality of time steps comprise health-related data associated with a patient, the health-related data comprising: activity data identifying distances travelled by the patient, or health-related images, and wherein the conditions in the predetermined set of conditions are conditions that are satisfied when a health-related event occurs in association with the patient, wherein the health related event is a heart attack or stroke. one or more recurrent neural network layers and one or more logistic regression nodes, said layers and nodes trained on the same set of labeled training sequences; wherein the one or more recurrent neural network layers are configured to, for each of the plurality of time steps: receive the input at the time step; and collectively process the input at the time step to generate a network internal state for the time step; receive the input at the time step; and collectively process the input at the time step to generate a network internal state for the time step; wherein each of the logistic regression nodes corresponds to a respective condition from a predetermined set of conditions, and wherein each of the logistic regression nodes is configured to, for each of the plurality of time steps: receive the network internal state for the time step; and process the network internal state for the time step in accordance with current values of a set of parameters of the logistic regression node to generate a future condition score for the corresponding condition for the time step, wherein the future condition score for the corresponding condition represents a likelihood that the corresponding condition will be satisfied within a specified time period of the input at the time step, receive the network internal state for the time step; and process the network internal state for the time step in accordance with current values of a set of parameters of the logistic regression node to generate a future condition score for the corresponding condition for the time step, wherein the future condition score for the corresponding condition represents a likelihood that the corresponding condition will be satisfied within a specified time period of the input at the time step, wherein the inputs at the plurality of time steps comprise health-related data associated with a patient, the health-related data comprising: activity data identifying distances travelled by the patient, or health-related images, activity data identifying distances travelled by the patient, or health-related images, and wherein the conditions in the predetermined set of conditions are conditions that are satisfied when a health-related event occurs in association with the patient, wherein the health related event is a heart attack or stroke.