Radiomics combined with clinical characteristics predicted the progression-free survival time in first-line targeted therapy for advanced non-small cell lung cancer with EGFR mutation

OBJECTIVE: This study was to explore the most appropriate radiomics modeling method to predict the progression-free survival of EGFR-TKI treatment in advanced non-small cell lung cancer with EGFR mutations. Different machine learning methods may vary considerably and the selection of a proper model...

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Detalles Bibliográficos
Autores principales: Zhu, Jian-man, Sun, Lei, Wang, Linjing, Zhou, Tong-Chong, Yuan, Yawei, Zhen, Xin, Liao, Zhi-Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research Note
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9008953/
https://www.ncbi.nlm.nih.gov/pubmed/35422007
http://dx.doi.org/10.1186/s13104-022-06019-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9008953/
https://www.ncbi.nlm.nih.gov/pubmed/35422007
http://dx.doi.org/10.1186/s13104-022-06019-x

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