Role of Radiomics Features and Machine Learning for the Histological Classification of Stage I and Stage II NSCLC at [(18)F]FDG PET/CT: A Comparison between Two PET/CT Scanners

The aim of this study was to compare two different PET/CT tomographs for the evaluation of the role of radiomics features (RaF) and machine learning (ML) in the prediction of the histological classification of stage I and II non-small-cell lung cancer (NSCLC) at baseline [(18)F]FDG PET/CT. A total o...

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Detalles Bibliográficos
Autores principales: Dondi, Francesco, Gatta, Roberto, Albano, Domenico, Bellini, Pietro, Camoni, Luca, Treglia, Giorgio, Bertagna, Francesco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9820870/
https://www.ncbi.nlm.nih.gov/pubmed/36615053
http://dx.doi.org/10.3390/jcm12010255

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9820870/
https://www.ncbi.nlm.nih.gov/pubmed/36615053
http://dx.doi.org/10.3390/jcm12010255

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