Deep learning prediction of radiation-induced xerostomia and personalized outcome-driven treatment planning in head and neck cancer
The proposed atlas-normalized model achieved robust discrimination, and a 9-case plan-refinement analysis showed that CAM- and GM-derived spatial information could be translated into clinically constrained avoidance objectives that reduced the model-predicted RIX probability while preserving specified target and organs...