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Robust Collaborative Clustering of Subjects and Radiomic Features for Cancer Prognosis

Feature dimensionality reduction plays an important role in radiomic studies with a large number of features. However, conventional radiomic approaches may suffer from noise, and feature dimensionality reduction techniques are not equipped to utilize latent supervision information of patient data un...

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Detalhes bibliográficos
Publicado no:IEEE Trans Biomed Eng
Main Authors: Liu, Hangfan, Li, Hongming, Habes, Mohamad, Li, Yuemeng, Boimel, Pamela, Janopaul-Naylor, James, Xiao, Ying, Ben-Josef, Edgar, Fan, Yong
Formato: Artigo
Idioma:Inglês
Publicado em: 2020
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC8048106/
https://ncbi.nlm.nih.gov/pubmed/31995474
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/TBME.2020.2969839
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