Enhanced prediction of gene mutation and risk stratification in non-small-cell lung cancer through dual-pathway fusion of radiomics and pathomics
We demonstrated that Nomogram which integrated radiomics, pathomics and clinical features, could be served as a noninvasive and reusable tool to precisely predict EGFR status and risk stratification in NSCLC.
Authors
- Hong Pan (ORCID: https://orcid.org/0000-0002-5063-7347)
- Hongguang Lu (ORCID: https://orcid.org/0000-0002-2911-762X)
- Ruisheng Ge
- Yang Teng (ORCID: https://orcid.org/0000-0002-2564-2662)
- Bei Lu (ORCID: https://orcid.org/0000-0001-8125-3461)
- Tong Zhang (ORCID: https://orcid.org/0000-0003-1036-7060)
- Lin Liu (ORCID: https://orcid.org/0000-0002-4613-3998)
- Chenglong Zheng
- Xin Yang (ORCID: https://orcid.org/0000-0003-3428-3806)
- Wei Meng (ORCID: https://orcid.org/0000-0002-1166-2216)
- Yang Ji (ORCID: https://orcid.org/0000-0003-3960-455X)
- Jiaheng Xu (ORCID: https://orcid.org/0009-0006-9541-0716)
Institutions
- Harbin Medical University (CN)
- Third Affiliated Hospital of Harbin Medical University (CN)
- Fourth Affiliated Hospital of Harbin Medical University (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-09-03
- DOI
- https://doi.org/10.3389/fonc.2025.1646851
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China