Handcrafted radiomics from multicenter CT scans achieves 0.77 AUC for predicting EGFR and KRAS mutations in lung cancer and generalizes better than deep features.
Machine learning evaluation metric discrepancies across programming languages and their components in medical imaging domains: need for standardization
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Robust Multicenter CT Radiogenomics for Dual EGFR and KRAS Prediction in Lung Cancer with Stability-Aware Modeling and SHAP Interpretation
Handcrafted radiomics from multicenter CT scans achieves 0.77 AUC for predicting EGFR and KRAS mutations in lung cancer and generalizes better than deep features.