Patent ID: 11922277
Assignee: OSAKA UNIVERSITY
Field: Medical technology (Instruments)
Classification: CPC A  G | IPC G

Claim 3:
4. A non-transitory recording medium storing a program for causing a computer to execute processing to obtain an improved differentiation model based on an accuracy of a single differentiation model to be derived by machine learning, the computer including a processor, a memory for storing the program and an interface configured to communicate with a database storing brainwave data samples of subjects respectively associated with pain labels, the processing comprising:
a. dividing, by the processor, the brainwave data samples of the subjects into a first predetermined number of first groups;
b. determining, by the processor, a hyperparameter of a penalty term of the single differentiation model by executing k-fold cross-validation of supervised machine learning based on the brainwave data samples of the first groups according to the pain labels, where k equals to the first predetermined number;
c. generating, by the processor, the single differentiation model by using the determined hyperparameter and all the brainwave data samples of the subjects to calculate first differentiation accuracy for each of the subjects;
d. ranking, by the processor, the subjects based on the first differentiation accuracy to group the subjects into a second predetermined number of second groups according to ranking order;
e. determining, by the processor, an individual hyperparameter of the penalty term of an individual differentiation model for each of the second groups by executing l-fold cross-validation of supervised machine learning on the brainwave data samples of each of the second groups, where l is a predetermined number common to the second groups;
f. generating, by the processor, the individual differentiation model for each of the second groups using the determined individual hyperparameter; and
g. identifying a differentiation maximum (MAX) model for each of the subjects among the individual differentiation models by searching for the individual differentiation model with the highest second differentiation accuracy for each of the subjects.