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

Claim 4:
5. A system for executing a computer-implemented method to obtain an improved differentiation model based on an accuracy of a single differentiation model to be derived by machine learning, the system comprising:
a processor;
a memory for storing a machine learning program; and
an interface configured to communicate with a database storing brainwave data samples of subjects respectively associated with pain labels;
wherein the processor configured to:
divide the brainwave data samples into a predetermined number of first groups;
determine a hyperparameter of a penalty term of the single differentiation model by executing k-fold cross-validation of supervised machine learning on the brainwave data samples of the first groups according to the pain labels, where k equals to the first predetermined number;

generate 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;
rank the subjects based on the first differentiation accuracy to group the subjects into a second predetermined number of second groups according to ranking order;
determine 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;
generate the individual differentiation model for each of the second groups using the determined individual hyperparameter; and
identify 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.