Explainable 18F-FDG PET/CT radiomics model for predicting EGFR mutation status in lung adenocarcinoma: a two-center study
The explainable EGFR mutation status prediction model have certain clinical practicability and good generalization performance, which may help in the timely selection of treatment options and prognosis prediction in patients with LUAD.
Authors
- Yu-sen Fang
- Qiufang Liu
- Panli Li
- Nan Li (ORCID: https://orcid.org/0000-0001-7619-1139)
- Shaoli Song (ORCID: https://orcid.org/0000-0003-2544-7522)
- Jianping Zhang (ORCID: https://orcid.org/0000-0003-2012-7837)
- Yan Zuo
- Linjie Bian (ORCID: https://orcid.org/0000-0002-1709-2939)
Institutions
- Shanghai Medical College of Fudan University (CN)
- Shanghai Normal University (CN)
- Fudan University (CN)
- Fudan University Shanghai Cancer Center (CN)
- United Imaging Healthcare (China) (CN)
Publication Details
- Journal
- Journal of Cancer Research and Clinical Oncology
- Published
- 2024-10-22
- DOI
- https://doi.org/10.1007/s00432-024-05998-7
- Citations
- 4
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 1.62
Funders
- Science and Technology Commission of Shanghai Municipality