A machine learning-based predictive model for postoperative pulmonary complications in lung cancer and its SHAP interpretation.

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Title: A machine learning-based predictive model for postoperative pulmonary complications in lung cancer and its SHAP interpretation.
Authors: Sha Y; Department of Anesthesiology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Peking University Cancer Hospital Yunnan, Kunming, China., Huangfu Z; Department of Anesthesiology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Peking University Cancer Hospital Yunnan, Kunming, China., Gu X; Department of Anesthesiology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Peking University Cancer Hospital Yunnan, Kunming, China., Tang B; Department of Anesthesiology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Peking University Cancer Hospital Yunnan, Kunming, China., Lv Z; Department of Anesthesiology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Peking University Cancer Hospital Yunnan, Kunming, China., Li Y; Department of Anesthesiology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Peking University Cancer Hospital Yunnan, Kunming, China., Yang J; Department of Anesthesiology, Simao District People's Hospital of Pu'er City, Pu'er, China., Yang J; Department of Anesthesiology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Peking University Cancer Hospital Yunnan, Kunming, China., Shao S; Department of Anesthesiology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Peking University Cancer Hospital Yunnan, Kunming, China., Wang Z; Department of Anesthesiology, The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Peking University Cancer Hospital Yunnan, Kunming, China.
Source: Frontiers in oncology [Front Oncol] 2026 Mar 13; Vol. 16, pp. 1749808. Date of Electronic Publication: 2026 Mar 13 (Print Publication: 2026).
Publication Type: Journal Article
Journal Info: Publisher: Frontiers Research Foundation] Country of Publication: Switzerland NLM ID: 101568867 Publication Model: eCollection Cited Medium: Print ISSN: 2234-943X (Print) Linking ISSN: 2234943X NLM ISO Abbreviation: Front Oncol Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
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ISSN:2234-943X
DOI:10.3389/fonc.2026.1749808