DISEASE AFFECTION DETERMINATION DEVICE, DISEASE AFFECTION DETERMINATION METHOD, AND DISEASE AFFECTION DETERMINATION PROGRAM

摘要

To enable disease affection determination by using a neural network to perform learning using data of the expression levels of biomarkers, and to enable extraction of a feature biomarker for a disease by the neural network. Sample data in which respective expression levels of a plurality of types of biomarkers are recorded for each individual is acquired, a learned model in which affection of diseases is determinable obtained in advance by performing machine learning using training data is generated, a plurality of sample data to which label information of disease affection is attached is input to the learned model and calculation is performed, the degrees of importance of respective feature of a plurality of biomarkers obtained with the learned model are quantified by affection determination calculation, for each sample data, and a predetermined number of biomarkers are extracted as feature biomarkers regarding the disease on the basis of the quantified degrees of importance of all the sample data for each biomarker.