CT-based radiomics in predicting pathological response in non-small cell lung cancer patients receiving neoadjuvant immunotherapy

OBJECTIVES: In radiomics, high-throughput algorithms extract objective quantitative features from medical images. In this study, we evaluated CT-based radiomics features, clinical features, in-depth learning features, and a combination of features for predicting a good pathological response (GPR) in...

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Detalles Bibliográficos
Autores principales: Lin, Qian, Wu, Hai Jun, Song, Qi Shi, Tang, Yu Kai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9577189/
https://www.ncbi.nlm.nih.gov/pubmed/36267975
http://dx.doi.org/10.3389/fonc.2022.937277

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9577189/
https://www.ncbi.nlm.nih.gov/pubmed/36267975
http://dx.doi.org/10.3389/fonc.2022.937277

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