TabPFN-driven ternary classification of stage IA lung adenocarcinoma subtypes using AI-derived histogram features a retrospective multicenter cohort study
TabPFN enables robust, generalizable ternary classification of LUAD subtypes, surpassing conventional ML and frozen section analysis. Its integration with automated histogram analysis offers a scalable solution for preoperative stratification of early-stage lung cancer.
Authors
- Guotian Pei (ORCID: https://orcid.org/0000-0001-7021-3624)
- S. Wang
- Dawei Wang (ORCID: https://orcid.org/0000-0001-7547-0689)
- Yuqing Huang (ORCID: https://orcid.org/0009-0007-2696-5782)
- Yingshun Yang
- Shushi Meng
- Wen Tang
- Lei Liu
- Kunkun Sun
- Jun Liu
Institutions
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Peking University (CN)
- Peking Union Medical College Hospital (CN)
- InferVision (China) (CN)
- Peking University People's Hospital (CN)
- Beijing Haidian Hospital (CN)
Publication Details
- Journal
- International Journal of Surgery
- Published
- 2026-02-03
- DOI
- https://doi.org/10.1097/js9.0000000000004585
- Primary Topic
- Lung Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00