Application of artificial intelligence-assisted education for postoperative pulmonary rehabilitation: a hybrid model of AI and nurse-driven support

OBJECTIVE: To explore the clinical value of AI-assisted pulmonary rehabilitation education in patients undergoing thoracoscopic surgery for lung cancer. METHODS: This was a non-randomized, two-period comparative study comparing AI-assisted education with routine education for postoperative pulmonary rehabilitation in lung cancer patients. Patients who underwent thoracoscopic radical lung cancer surgery in a Chinese general hospital between January and December 2024 were selected. Based on the type of education received, patients were divided into the routine education group and the AI-assisted education group. Relevant information was collected through electronic medical records. RESULTS: A total of 128 cases were included, with 65 in the routine group and 63 in the AI-assisted group. Baseline data showed no significant intergroup differences. Compared with routine education, AI-assisted education significantly improved patient adherence to exercise training (51.6 ± 7.5 vs. 43.1 ± 6.4, P < 0.001) and postoperative self-efficacy (91.3 ± 6.7 vs. 77.2 ± 7.0, P < 0.001). The incidence of complications was lower in the AI-assisted group (4.8% vs. 15.4%,). Psychological assessment revealed lower depression and anxiety scores among patients receiving AI-assisted education (depression: 8.4 ± 2.6 vs. 10.1 ± 3.4, P = 0.001; anxiety: 8.6 ± 2.3 vs. 11.5 ± 2.5, P < 0.001). CONCLUSION: The collaboration between artificial intelligence-assisted education and nursing staff in the lung rehabilitation education model can enhance postoperative rehabilitation adherence and self-efficacy in lung cancer patients. Further studies, including randomized controlled trials, are needed to confirm AI's benefits and long-term impact on patient outcomes.