Computed tomography radiomics signature via machine learning predicts RRM2 and overall survival in hepatocellular carcinoma

BACKGROUND: Radiomics can be used to noninvasively predict molecular markers to address the clinical dilemma that some patients cannot accept invasive procedures. This research evaluated the prognostic significance of the expression level of ribonucleotide reductase regulatory subunit M2 (RRM2) in i...

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Detalles Bibliográficos
Autores principales: Li, Qian, Long, Xiawei, Lin, Yan, Liang, Rong, Li, Yongqiang, Ge, Lianying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10331770/
https://www.ncbi.nlm.nih.gov/pubmed/37435222
http://dx.doi.org/10.21037/jgo-23-460

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10331770/
https://www.ncbi.nlm.nih.gov/pubmed/37435222
http://dx.doi.org/10.21037/jgo-23-460

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