[引用][C] A combined radiomics-dosiomics machine learning approach improves prediction of radiation pneumonitis compared to DVH data in lung cancer patients

N Chopra, T Dou, G Sharp, E Sajo… - International Journal of …, 2020 - redjournal.org
Results While the dosiomics model performance was comparable to the DVH model, we find
that a radiomics+ dosiomics model with features extracted from the V 20 ROI (AUC= 0.713)
and combined V 20+ V 5 radiomics+ dosiomics model (AUC= 0.708) outperform the DVH
only model (AUC= 0.63). In addition, radiomics+ dosiomics+ clinical model with features
generated from the V 20 ROI (AUC= 0.771) and the radiomics+ dosiomics+ clinical model
with combined features from V 20 and V 5 ROI (AUC= 0.763) fared better than the clinical …
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