Machine learning predictive models and risk factors for lymph node metastasis in non-small cell lung cancer
The predictive model based on GLM can be used to precisely predict the probability of LNM in NSCLC patients, which was proven effective in all subgroup analyses according to T staging.
Authors
- Jiajun Wu (ORCID: https://orcid.org/0000-0002-9847-2510)
- Mao-Yan Si
- Bo Wu (ORCID: https://orcid.org/0000-0002-7818-2807)
- Wenxiong Zhang (ORCID: https://orcid.org/0000-0003-2962-0847)
- Yihui Zhu (ORCID: https://orcid.org/0000-0002-5928-279X)
- Zhuozheng Hu
- Zhicheng Wu (ORCID: https://orcid.org/0000-0003-1596-8869)
- Weijun Zhou (ORCID: https://orcid.org/0009-0001-8352-8200)
- Xiying Cao (ORCID: https://orcid.org/0000-0002-9756-5221)
Institutions
- Nanchang University (CN)
- First Affiliated Hospital of Jiangxi Medical College (CN)
- Second Affiliated Hospital of Nanchang University (CN)
- Chinese University of Hong Kong, Shenzhen (CN)
- First Affiliated Hospital of Gannan Medical University (CN)
- First Affiliated Hospital of Nanchang University (CN)
Publication Details
- Journal
- BMC Pulmonary Medicine
- Published
- 2024-10-22
- DOI
- https://doi.org/10.1186/s12890-024-03345-7
- Citations
- 4
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.62
Funders
- Natural Science Foundation of Jiangxi Province