Fig. 2: Analysis of the correlations between radiomics and non-imaging features. | Nature Communications

Fig. 2: Analysis of the correlations between radiomics and non-imaging features.

From: Integrated radiogenomics models predict response to neoadjuvant chemotherapy in high grade serous ovarian cancer

Fig. 2: Analysis of the correlations between radiomics and non-imaging features.The alternative text for this image may have been generated using AI.

a Spearman correlation coefficients between imaging (rows) and clinical and biological features (columns), both clustered using a hierarchical approach, using the training cohort. b Composition and characteristics of the six identified imaging feature clusters. Polar plots indicate the relative contribution of the different classes of imaging features. Scatter plots show the feature of each cluster with the highest Spearman correlation with volumetric treatment response. Each features is illustrated by displaying one slice from the patient with the maximum value (left), and one from the patient with the minimum value (right). Source data are provided as a Source Data file. p values are two-sided and corrected for multiple comparisons.

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