The predictive value of [(18)F]FDG PET/CT radiomics combined with clinical features for EGFR mutation status in different clinical staging of lung adenocarcinoma

BACKGROUND: This study aims to construct radiomics models based on [(18)F]FDG PET/CT using multiple machine learning methods to predict the EGFR mutation status of lung adenocarcinoma and evaluate whether incorporating clinical parameters can improve the performance of radiomics models. METHODS: A t...

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Detalles Bibliográficos
Autores principales: Gao, Jianxiong, Niu, Rong, Shi, Yunmei, Shao, Xiaoliang, Jiang, Zhenxing, Ge, Xinyu, Wang, Yuetao, Shao, Xiaonan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10073367/
https://www.ncbi.nlm.nih.gov/pubmed/37014500
http://dx.doi.org/10.1186/s13550-023-00977-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10073367/
https://www.ncbi.nlm.nih.gov/pubmed/37014500
http://dx.doi.org/10.1186/s13550-023-00977-4

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