Objective To explore the application effects of artificial intelligence (AI)-empowered teaching based on knowledge graphs in the neurology course, and evaluate its impact on medical students' learning outcomes, learning engagement and comprehensive quality cultivation.

Methods Two teaching classes, class A and class B of the 2021 grade of clinical medicine at Bengbu Medical University, were selected as the research subjects, and randomly divided into the observation group (n = 79) and control group (n = 78). The observation group adopted the AI-empowered intelligent teaching model based on knowledge graphs, while the control group adopted the traditional lecture teaching. After the course, the theoretical examination scores and learning behavior data between two groups were compared, and the teaching effect and satisfaction were evaluated through questionnaires.

Results The theoretical examination scores in the observation group were significantly higher than those in the control group (P ＜ 0.01). The quality score of the learning path completion in the observation group was positively correlated with the frequency of platform usage (r = 0.699, P ＜ 0.01), and also positively correlated with the duration of online learning (r = 0.600, P ＜ 0.01). The results of questionnaire survey showed that the recognition degrees of the professional knowledge mastery (83.5%), stimulation of learning interest (88.6%), improvement of ideological and political quality (78.5%) and teamwork ability (75.9%) in the observation group was higher than that those in the control group (P ＜ 0.01). The teaching satisfaction of the observation group was higher than that of the control group (P ＜ 0.01).

Conclusions AI-empowered teaching based on knowledge graphs can effectively improve the teaching quality of the neurology course, promote students' understanding and absorption of professional knowledge, enhance learning engagement, and also help cultivate students' comprehensive qualities.