Machine learning-based FDG PET-CT radiomics for outcome prediction in larynx and hypopharynx squamous cell carcinoma

•Radiomic features predict disease recurrence in larynx/hypopharyx cancer. •Machine-learning methods selected the radiomic/clinical features for the 4 models. •The 4 models were PET only, CT only, clinical features only and combined PET and CT. •The combined PET/CT radiomics model had the highest AUC value (0.94). AIM To determine whether machine learning-based radiomic feature analysis of baseline integrated 2-[18F]-fluoro-2-deoxy-d-glucose...