Incremental value of radiomics with machine learning to the existing prognostic models for predicting outcome in renal cell carcinoma

PURPOSE: To systematically evaluate the potential of radiomics coupled with machine-learning algorithms to improve the predictive power for overall survival (OS) of renal cell carcinoma (RCC). METHODS: A total of 689 RCC patients (281 in the training cohort, 225 in the validation cohort 1 and 183 in...

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Detalles Bibliográficos
Autores principales: Xing, Jiajun, Liu, Yiyang, Wang, Zhongyuan, Xu, Aiming, Su, Shifeng, Shen, Sipeng, Wang, Zengjun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Oncology
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10175776/
https://www.ncbi.nlm.nih.gov/pubmed/37188171
http://dx.doi.org/10.3389/fonc.2023.1036734

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10175776/
https://www.ncbi.nlm.nih.gov/pubmed/37188171
http://dx.doi.org/10.3389/fonc.2023.1036734

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