Differentiation of early-stage tumors from benign lesions manifesting as pure ground-glass nodule: a clinical prediction study based on AI-derived quantitative parameters
The clinical prediction nomogram, based on AI-derived quantitative parameters, visually displays an overall score to differentiate benign lesions from early-stage tumors manifesting as pGGN. This nomogram may serve as a convenient screening tool for clinical use and provides a reference for formulating individualized follow-up and treatment plans for patients with pGGN.
Authors
- Shuxiang Chen (ORCID: https://orcid.org/0000-0002-1058-4391)
- Wenfu Cao (ORCID: https://orcid.org/0000-0001-7539-4866)
- Yongxiu Tong
- Shuo Chen (ORCID: https://orcid.org/0000-0002-7243-0136)
- Yifan Chen (ORCID: https://orcid.org/0000-0001-5494-4435)
- Huijuan Zhang (ORCID: https://orcid.org/0000-0003-3703-5242)
Institutions
- Fujian Medical University (CN)
- Fujian Provincial Hospital (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-05-19
- DOI
- https://doi.org/10.3389/fonc.2025.1573735
- Primary Topic
- Lung Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Natural Science Foundation of Fujian Province
- Fujian Provincial Department of Science and Technology