Prediction of EGFR Mutation Status Based on (18)F-FDG PET/CT Imaging Using Deep Learning-Based Model in Lung Adenocarcinoma

OBJECTIVE: The purpose of this study was to develop a deep learning-based system to automatically predict epidermal growth factor receptor (EGFR) mutant lung adenocarcinoma in (18)F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT). METHODS: Three hundred and one lun...

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Detalles Bibliográficos
Autores principales: Yin, Guotao, Wang, Ziyang, Song, Yingchao, Li, Xiaofeng, Chen, Yiwen, Zhu, Lei, Su, Qian, Dai, Dong, Xu, Wengui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8340023/
https://www.ncbi.nlm.nih.gov/pubmed/34367993
http://dx.doi.org/10.3389/fonc.2021.709137

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8340023/
https://www.ncbi.nlm.nih.gov/pubmed/34367993
http://dx.doi.org/10.3389/fonc.2021.709137

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