Fusion of CT radiomics and autoantibody biomarkers for enhanced prediction of lung cancer diagnosis: a comprehensive study
The fusion of CT radiomics and autoantibody biomarkers significantly enhances the diagnostic performance for lung cancer. This integrated approach enhances early detection and reduces unnecessary interventions, paving the way for personalized treatment strategies. Future research should focus on clinical validation and optimization of this model to facilitate its implementation in routine clinical practice.
Authors
- Yiman Du
- Xianwu Xia (ORCID: https://orcid.org/0000-0003-3508-0816)
- Qianjin Hua
- Xiaowen Ma (ORCID: https://orcid.org/0009-0004-0749-3060)
- Haitao Jiang (ORCID: https://orcid.org/0000-0002-1715-7050)
- Lingling Wang (ORCID: https://orcid.org/0000-0002-4648-5790)
- Chibo Liu
- Jianlin Liu (ORCID: https://orcid.org/0000-0001-6513-0867)
- Chao He (ORCID: https://orcid.org/0000-0002-4629-4740)
- Jianjun Yuan (ORCID: https://orcid.org/0000-0003-1823-8239)
- Guoming Zhou
Institutions
- Wenzhou Medical University (CN)
- First Affiliated Hospital of Wenzhou Medical University (CN)
- Fudan University Shanghai Cancer Center (CN)
- First Affiliated Hospital of Jiangxi Medical College (CN)
- Zhejiang Cancer Hospital (CN)
- Taizhou Municipal Hospital (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-10-29
- DOI
- https://doi.org/10.3389/fonc.2025.1591156
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Science and Technology Department of Zhejiang Province