Predicting epidermal growth factor receptor mutation status of lung adenocarcinoma based on PET/CT images using deep learning
The PET/CT images based on trained CNNs effectively predict <i>EGFR</i> and non-<i>EGFR</i> mutations in LUAD. The deep learning predictive models could guide treatment options.
Authors
- Jiangyan Liu (ORCID: https://orcid.org/0000-0002-4553-4124)
- Weifang Kong (ORCID: https://orcid.org/0000-0002-0741-4551)
- Yongjun Luo
- Guojin Zhang (ORCID: https://orcid.org/0000-0002-4312-5212)
- Lele Huang
- Hongjun Xie (ORCID: https://orcid.org/0000-0001-6409-5983)
- Xin Zhang (ORCID: https://orcid.org/0000-0001-6388-9327)
Institutions
- University of Electronic Science and Technology of China (CN)
- Lanzhou University Second Hospital (CN)
- Lanzhou University (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2024-12-13
- DOI
- https://doi.org/10.3389/fonc.2024.1458374
- Citations
- 3
- Primary Topic
- Lung Cancer Treatments and Mutations
- Type
- article
- Field-Weighted Citation Impact
- 1.26
Funders
- Lanzhou University
- National Natural Science Foundation of China