Machine learning method of neural network predicting mechanism of action of drug, and method of predicting mechanism of action of drug by using the neural network

A computing device comprising:

• a communication unit;
• and
• a processor coupled to the communication unit,
• wherein the processor is configured to perform processes including:
• from a plurality of medical images X0, . . . Xt obtained in time series, outputting first compressed data Z0, . . . Zt corresponding to the plurality of medical images X0, . . . Xt, each of the first compressed data having a smaller capacity than a corresponding medical image,
• wherein the plurality of medical images X0, . . . Xt are the medical images related to a brain of the subject;
• estimating second compressed data h0 by inputting first compressed data Z0 to a recurrent neural network;
• estimating second compressed data h1 corresponding to a predicted medical image X′i+1 at a time point i+1 after a time point i at which a medical image Xi was captured by inputting first compressed data Z;
• and second compressed data hi−1 to the recurrent neural network, for a period satisfying 0<i≤t, while increasing a value of i;
• and
• predicting the action mechanism of a drug for a subject by inputting second compressed data ht to a neural network learned to predict the action mechanism of the drug,
• wherein the second compressed data ht corresponds to a predicted medical image X′t+1, which reflects a change in a blood flow of the brain or an activity of the brain predicted to occur at a time point t+1 after a time point t.

A non-transitory computer program product for predicting an action mechanism of a drug from medical images of a subject, wherein the computer program product comprises a computer readable storage medium having program code embodied therein, and wherein the program code, when executed, performs operations, the operations comprising:

• from a plurality of medical images X0, . . . Xt obtained in time series, outputting first compressed data Z0, . . . Zt corresponding to the plurality of medical images X0, . . . Xt, each of the first compressed data having a smaller size than a corresponding medical image,
• wherein the plurality of medical images X0, . . . Xt are the medical images related to a brain of the subject;
• estimating second compressed data h0 by inputting first compressed data Z0 to a recurrent neural network;
• estimating second compressed data hi corresponding to a predicted medical image X′i+1 at a time point i+1 after a time point i at which a medical image Xi was captured by inputting first compressed data Z;
• and second compressed data hi−1 to the recurrent neural network, for a period satisfying 0<i≤t, while increasing a value of i;
• and
• predicting the action mechanism of the drug for the subject by inputting second compressed data ht to a neural network learned to predict the action mechanism of the drug, wherein the second compressed data ht corresponds to a predicted medical image X′t+1, which reflects a change in a blood flow of the brain or an activity of the brain predicted to occur at a time point t+1 after a time point t.