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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...
Autores principales: | Xing, Jiajun, Liu, Yiyang, Wang, Zhongyuan, Xu, Aiming, Su, Shifeng, Shen, Sipeng, Wang, Zengjun |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
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 |
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