The Challenge of Choosing the Best Classification Method in Radiomic Analyses: Recommendations and Applications to Lung Cancer CT Images

SIMPLE SUMMARY: Radiomics aims to extract high-dimensional features from clinical images and associate them to clinical outcomes. These associations may be further investigated with machine learning models; however, guidelines on the most suitable method to support clinical decisions are still missi...

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Detalles Bibliográficos
Autores principales: Corso, Federica, Tini, Giulia, Lo Presti, Giuliana, Garau, Noemi, De Angelis, Simone Pietro, Bellerba, Federica, Rinaldi, Lisa, Botta, Francesca, Rizzo, Stefania, Origgi, Daniela, Paganelli, Chiara, Cremonesi, Marta, Rampinelli, Cristiano, Bellomi, Massimo, Mazzarella, Luca, Pelicci, Pier Giuseppe, Gandini, Sara, Raimondi, Sara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8234634/
https://www.ncbi.nlm.nih.gov/pubmed/34205631
http://dx.doi.org/10.3390/cancers13123088

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8234634/
https://www.ncbi.nlm.nih.gov/pubmed/34205631
http://dx.doi.org/10.3390/cancers13123088

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