ObjectiveTo explore the teaching model of the "LungSmart" smart healthcare system in clinical pulmonology teaching and its effectiveness in enhancing the clinical reasoning skills of postgraduate students. MethodsA single-center, single-group pretest-posttest educational intervention study was conducted among 30 postgraduate students who participated in respiratory medicine-related teaching activities and enrolled in the "LungSmart" smart healthcare course at Shanghai Pulmonary Hospital from 2024 to 2025 academic year. The course was structured around three core components, namely an AI case repository, dynamic simulation, and immediate feedback, and was delivered over 16 weeks with a total of 64 class hours. Teaching effectiveness was assessed using pretest and posttest clinical reasoning ability scores, while students’ acceptance of the course was evaluated using a 5-point Likert questionnaire. ResultsAll 30 students completed the teaching activities and were included in the final analysis. The pretest score was (78.83±6.25) points, and the posttest score increased to (93.50±4.18) points, with a mean improvement of (14.67±7.06) points (95%CI, 12.03 to 17.30), indicating a statistically significant improvement after the intervention (t=11.37, P<0.001). A total of 30 valid questionnaires were collected at the end of the course, with a response rate of 100.0%. The overall satisfaction score was (4.67±0.15) points, and the mean scores for content satisfaction, practical value, interest stimulation, and professional competence were (4.72±0.23) points, (4.53±0.35) points, (4.72±0.39) points, and (4.75±0.43) points, respectively. ConclusionThese findings suggest that the clinical teaching model based on the "LungSmart" smart healthcare system is feasible and well accepted, and may help improve postgraduate students’ clinical reasoning ability.