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Insights into Imaging
Fig. 2 | Insights into Imaging

Fig. 2

From: Exploring a multiparameter MRI–based radiomics approach to predict tumor proliferation status of serous ovarian carcinoma

Fig. 2

Features retained after radiomics high-throughput feature dimension reduction. a MSE PATH, the dotted line represents the α value (1.9) with the smallest mean square error. b LASSO PATH, the radiomic features are determined according to the α value with the smallest mean square error. c Lasso coefficient of the features after radiomics high-throughput feature dimension reduction

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