Abstract: A diagnostic assistance apparatus according to an aspect of the present disclosure determines whether a body part of a target examinee captured in a target medical image is normal, by using a trained first classification model generated by unsupervised learning using a plurality of first learning medical images of normal cases and a trained second classification model generated by supervised learning using a plurality of learning data sets including normal cases and abnormal cases.