BACKGROUND: The rising global cancer burden has led to an increasing demand for imaging tests such as [^(18)F]fluorodeoxyglucose ([^(18)F]FDG)-PET-CT. To aid imaging specialists in dealing with high scan volumes, we aimed to train a deep learning artificial intelligence algorithm to classify [^(18)F]FDG-PET-CT scans of patients with lymphoma with or without hypermetabolic tumour …