ArticleJournal of cardiothoracic surgery2026
Application of artificial intelligence-assisted education for postoperative pulmonary rehabilitation: a hybrid model of AI and nurse-driven support.
Article in Journal of cardiothoracic surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo explore the clinical value of AI-assisted pulmonary rehabilitation education in patients undergoing thoracoscopic surgery for lung cancer.
methodsThis 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.
resultsA 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).
conclusionThe 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.