Fig. 6: Neural network radiomics classifier for predicting MOFS subtypes. | Nature Communications

Fig. 6: Neural network radiomics classifier for predicting MOFS subtypes.

From: Multimodal fusion of radio-pathology and proteogenomics identify integrated glioma subtypes with prognostic and therapeutic opportunities

Fig. 6

A Workflow for constructing a deep neural network (DNN) model using 22 radiomic features from MRI images, optimized through elastic backpropagation. B Confusion matrices showing DNN model accuracy on FAHZZU1 training, FAHZZU1 testing, and FAHZZU2 validation cohorts. C Kaplan-Meier survival analysis of predicted MOFS subtypes in the FAHZZU3 cohort, demonstrating significant survival differences (n = 992, P = 0.00025). Statistic tests: log-rank test. D Web tool interface for predicting MOFS subtypes using radiomic features.

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