Machine Learning for Classification in Lung Cancer Using Routine Clinical and Laboratory Data
This study presented a robust, non-invasive machine learning model for lung cancer subtype classification, addressing critical gaps in clinical practice for biopsy-ineligible patients. A web-based calculator was developed to facilitate clinical application. Nonetheless, future multicenter validation is warranted to expand the generalizability of this model and promote adoption in diverse healthcare settings.
Authors
- Wang Zuo
- Yulin Liao (ORCID: https://orcid.org/0000-0001-5961-390X)
- Liwei Zhao (ORCID: https://orcid.org/0000-0003-3491-2027)
- Chang Liu (ORCID: https://orcid.org/0000-0001-5144-1736)
- Xiaoling Liu (ORCID: https://orcid.org/0000-0002-5051-4574)
- Dongsheng Wang (ORCID: https://orcid.org/0000-0002-6409-5366)
- Jie Yang (ORCID: https://orcid.org/0000-0001-7255-3147)
- Lichun Wu
Institutions
- Sichuan Cancer Hospital (CN)
Publication Details
- Journal
- Annals of Surgical Oncology
- Published
- 2025-12-03
- DOI
- https://doi.org/10.1245/s10434-025-18747-y
- Primary Topic
- Lung Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00