Self-Supervised Bayesian Multimodal Learning for Uncertainty-Aware Prediction of Radiation Pneumonitis
Accurate prediction of radiation-induced toxicity is crucial for optimizing radiotherapy outcomes. However, most existing predictive models rely on uni-modal data and deterministic models that are vulnerable to label noise and uncertainty. This study aims to...
Poster Program · Therapy Physics