Development of a machine learning-based model to predict prognosis of resected invasive pulmonary adenocarcinoma
Our study successfully constructed a machine-learning based prognostic model to predict DFS, which may provide oncologists with an effective tool for early medical intervention and survival improvement.
Authors
- Shenglin Ma
- Jiannan Qian
- Jingjing Xiang (ORCID: https://orcid.org/0000-0001-7191-7156)
- Xing Feng (ORCID: https://orcid.org/0000-0001-8226-3389)
- Xueqin Chen (ORCID: https://orcid.org/0000-0003-2299-6876)
- Jie Huang (ORCID: https://orcid.org/0000-0003-0381-1549)
- Jiafeng Liang
- Yunshan Zhong (ORCID: https://orcid.org/0000-0003-0268-4672)
- Rujun Xu
- Bing Xia
- Wen Meng
- Hong Jiang
- Yihui Ding
- Dongshan Wei
Institutions
- Sir Run Run Shaw Hospital (CN)
- Zhejiang University (CN)
Publication Details
- Journal
- Journal of Thoracic Disease
- Published
- 2025-12-01
- DOI
- https://doi.org/10.21037/jtd-2025-1669
- Primary Topic
- Lung Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00