Abstract: This study selected behavior characteristic indicators such as learning behavior, comprehensive ability and quality development. After data preprocessing, the random forest was used to select important eigenvalue, the improved entropy weight method was used to weight the selected important eigenvalue, and the cluster analysis was used to construct the student group portrait based on the whole process education data. The application prospect of student portraits based on artificial intelligence technology in basic medical education was discussed. Research has found the research on the construction of student portraits based on artificial intelligence technology provides new reform ideas for undergraduate and graduate education of basic medicine, and promotes the development of medical education.

Key words: Student portraits, Random forest, Basic medicine, Behavioral characteristics, Characteristic index, Cluster analysis