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Fig. 2 | Cancer Imaging

Fig. 2

From: Development and validation of a machine learning-based 18F-fluorodeoxyglucose PET/CT radiomics signature for predicting gastric cancer survival

Fig. 2

The workflow of the study. (a) Partialiegel Rlihood deviation values with respect to different λ values in the LASSO model. (b) Select the optimal λ value. (c) Rank the importance of each feature in the RSF model. PET: Positron emission tomography; LASSO: Least absolute shrinkage and selection operator; RSF: Random survival forest

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Cancer Imaging

ISSN: 1470-7330

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