Mohamed Naser

My research focuses on developing artificial intelligence (AI), machine learning (ML), and deep learning (DL) models to optimize cancer treatment, predict patient outcomes, and improve clinical decision-making. I specialize in quantitative medical imaging, radiomics, and computational oncology, with a particular emphasis on head and neck cancer (HNC) and applications in radiotherapy, treatment toxicity reduction, and risk stratification. Current projects include deep learning-based tumor segmentation in PET/CT and multiparametric MRI, radiopathomic risk stratification using uncertainty-aware AI models, image-based normal tissue injury and lymphedema/fibrosis severity assessment, and automated sarcopenia assessment for personalized treatment planning.