Medical information processing apparatus, medical information processing method, and non-transitory computer-readable storage medium storing program

A medical information processing apparatus comprising:

• processing circuitry configured to:
• perform processing using a trained model that is generated by machine learning with a plurality of training data;
• acquire first attribute data indicating at least one attribute of an object-to-be-trained related to the plurality of training data that are used for generating the trained model;
• acquire second attribute data indicating at least one attribute of an object-to-be-diagnosed;
• and
• perform the processing using the trained model based on goodness of fit that is an index indicating degree of matching between the first attribute data and the second attribute data, wherein
• the at least one attribute of the object-to-be-trained comprises a plurality of types of attributes;
• and
• the processing circuitry is configured to perform processing of issuing a warning to a user or other alternative processing when the at least one attribute of the object-to-be-diagnosed is a specific attribute and the goodness of fit of the specific attribute is equal to or less than a predetermined value, the alternative processing being processing that does not use the trained model.

A medical information processing method comprising:

• performing processing using a trained model that is generated by machine learning with a plurality of training data;
• acquiring first attribute data indicating at least one attribute of an object-to-be-trained related to the plurality of training data that are used for generating the trained model;
• acquiring second attribute data indicating an attribute of an object-to-be-diagnosed;
• and
• performing the processing on input-data of the object-to-be-diagnosed based on goodness of fit that is an index indicating degree of matching between the first attribute data and the second attribute data, wherein
• the at least one attribute of the object-to-be-trained comprises a plurality of types of attributes;
• and
• the goodness of fit is determined based on (i) a distribution range of the first attribute data calculated for each of the plurality of types of attributes of the object-to-be-trained and (ii) number of types of attributes for which the second attribute data are outside the distribution range.

A medical information processing method comprising:

• performing processing using a trained model that is generated by machine learning with a plurality of training data;
• acquiring first attribute data indicating at least one attribute of an object-to-be-trained related to the plurality of training data that are used for generating the trained model;
• acquiring second attribute data indicating an attribute of an object-to-be-diagnosed;
• and
• performing the processing on input-data of the object-to-be-diagnosed based on goodness of fit that is an index indicating degree of matching between the first attribute data and the second attribute data, wherein
• the at least one attribute of the object-to-be-trained comprises a plurality of types of attributes;
• and
• the method further comprises performing processing of issuing a warning to a user or other alternative processing when the at least one attribute of the object-to-be-diagnosed is a specific attribute and the goodness of fit of the specific attribute is equal to or less than a predetermined value, the alternative processing being processing that does not use the trained model.