INTERVENTION CONTENT ESTIMATION DEVICE, METHOD, AND PROGRAM

An object of an aspect of the present invention is to enable estimation of more effective intervention content in order to make a person's health state approximate to an ideal health state, and in a learning phase, measurement values and target values of a health state for a plurality of days in the past are sequentially input to a learning machine configured by a multilayer neural network, and the learning machine is caused to perform learning such that a target achievement expectation value obtained by using a success rate that allows the user's health state to approximate to an ideal health state, continuity that allows the health state approximate to the ideal health state to be maintained, and a target value of the health state to be subsequently recommended and the target achievement expectation value thereof that reflect a temporal change in the health state and a history of interventions until a present time are output. In an estimation phase, measurement values and target values of the user's health state in the last three days are input to the estimation model after learning, and the target value of the health state to be recommended, which is output from the estimation model at this time, is presented to the user.