Abstract:

 Objective　To investigate the practical effect of constructing an intelligent teaching system for the respiratory diseases course based on knowledge graphs and artificial intelligence (AI), aiming to address challenges in traditional teaching such as abstract nature of theoretical systems, limited clinical practice opportunities, and a single assessment mechanisms, thereby promoting the intelligent transformation of medical education.Methods　Undergraduate majoring in Clinical Medicine in the 2021 and 2022 cohorts at Chongqing Medical University were selected as the study subjects. An intelligent teaching platform based on knowledge graph and AI technologies was constructed and applied. The effectiveness of the teaching reform was evaluated by comparing indicators between the two cohorts, including classroom participation, theoretical and skill examination scores, Mini-CEX pass rates, and participation in innovation competitions.Results　Following the teaching practice, the application rate of knowledge graph and AI tools among students reached 100%; classroom participation increased from 82.41% to 100%; the Mini-CEX pass rate rose from 75.93% to 97.09%; and the number of participants in medical innovation competitions increased from 5 to 22. All differences were statistically significant (P<0.05).Conclusion　The intelligent teaching system based on knowledge graphs and AI effectively enhances students' classroom participation, clinical practice abilities, and learning initiative. It promotes the reconstruction of a "theory-practice-evaluation" trinity teaching paradigm, providing a feasible pathway and practical reference for the intelligent teaching reform of the respiratory diseases courses.

Key words:

 , knowledge graph｜ artificial intelligence｜respiratory system diseases｜intelligentization｜ teaching practice