IEEE Transactions on Biomedical Engineering

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Robust Collaborative Clustering of Subjects and Radiomic Features for Cancer Prognosis
A robust collaborative clustering method has been developed in a Bayesian framework to simultaneously cluster patients and imaging features into distinct groups respectively, aiming to learn a compact set of discriminative features in radiomics studies. Experiments on synthetic data have demonstrated the effectiveness of the proposed approach in data clustering, and evaluation results on an FDG-PET/CT dataset of rectal cancer patients have demonstrated that the proposed method outperforms alternative methods in terms of both patient stratification and prediction of patient clinical outcomes... Read more