Comparative performances of machine learning algorithms in radiomics and impacting factors

There are no current recommendations on which machine learning (ML) algorithms should be used in radiomics. The objective was to compare performances of ML algorithms in radiomics when applied to different clinical questions to determine whether some strategies could give the best and most stable pe...

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Detalles Bibliográficos
Autores principales: Decoux, Antoine, Duron, Loic, Habert, Paul, Roblot, Victoire, Arsovic, Emina, Chassagnon, Guillaume, Arnoux, Armelle, Fournier, Laure
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10462640/
https://www.ncbi.nlm.nih.gov/pubmed/37640728
http://dx.doi.org/10.1038/s41598-023-39738-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10462640/
https://www.ncbi.nlm.nih.gov/pubmed/37640728
http://dx.doi.org/10.1038/s41598-023-39738-7

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