… To perform a descriptive analysis of the radiomic features, we used unsupervised clustering
… that are correlated with prognosis by using radiomic signatures. We validated our model in …

… prognosis (19, 20, 21). In this study, unsupervised consensus clustering was used to establish
radiomics signatures, … The radiomics signatures generated by consensus clustering could …

… We assessed the prognostic accuracy of the radiomic signature … For feature selection,
consensus clustering method was … radiomic feature was selected from each of the four feature …

… -radiomics signature for the prognosis of LRC in patients with locally advanced HNSCC that
received primary RCTx. Using stability analysis and clustering … -small cell lung cancer on a …

… prognostic value for patients with non-small cell lung cancer (delta … -normalisation of the
imaging features and feature clustering. … The CT-based radiomic signatures developed in this …

… extraction to obtain prognostic patient information 1 . … importance of feature aggregation in
the context of lung cancer. … 50\) clusters (ie visual words) as a very large number of cluster is …

… study, unsupervised clustering of radiomic features … radiomic analysis linking radiomic
signatures to the tumor immune markers prognostic for overall survival has been described in lung …

… into the lung), iso_exterior (expansion into lung and soft tissue), … Identified radiomics features
prognostic for survival in … Computed tomography-derived radiomic signature of head and …

… hands were at either side of the head in a supine position from the … of radiomics features (N
= 7) on the x-axis reveals clusters of … Our radiomics method revealed lung nodules in a non-…

… The radiomics feature analysis consisted of cluster analysis … predict pathological response
in non-small cell lung cancer. … sensorineural hearing loss in head and neck cancer patients: A …