Predicting postoperative complications after pneumonectomy using machine learning: a 10-year study
The combination of machine-learning models and nomograms may contribute to the early prediction and reduction in the incidence of PCNC.
Authors
- Jiangang Yu
- Wenfei Tan (ORCID: https://orcid.org/0000-0001-9679-1406)
- Shiyang Xie (ORCID: https://orcid.org/0000-0001-7019-040X)
- Yong Cui (ORCID: https://orcid.org/0000-0002-3658-1770)
- Shun Xu (ORCID: https://orcid.org/0000-0002-5514-7726)
- Wenya Li (ORCID: https://orcid.org/0000-0002-5067-843X)
- Yaxuan Wang (ORCID: https://orcid.org/0000-0002-0996-096X)
- He Wang (ORCID: https://orcid.org/0009-0003-3964-0785)
- Aika Guan
- Jiayun Liu
Institutions
- Queen's University (CA)
- First Hospital of China Medical University (CN)
Publication Details
- Journal
- Annals of Medicine
- Published
- 2025-04-07
- DOI
- https://doi.org/10.1080/07853890.2025.2487636
- Citations
- 4
- Primary Topic
- Cardiac, Anesthesia and Surgical Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 5.55
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Liaoning Province