• Tricia Chinnery, Andrew Arifin, Keng Yeow Tay, Andrew Leung, Anthony C Nichols, David A Palma, Sarah A Mattonen, and Pencilla Lang.
• Department of Medical Biophysics, 6221Western University, London, Ontario, Canada.
• Can Assoc Radiol J. 2021 Feb 1; 72 (1): 73-85.

AbstractArtificial intelligence (AI)-based models have become a growing area of interest in predictive medicine and have the potential to aid physician decision-making to improve patient outcomes. Imaging and radiomics play an increasingly important role in these models. This review summarizes recent developments in the field of radiomics for AI in head and neck cancer. Prediction models for oncologic outcomes, treatment toxicity, and pathological findings have all been created. Exploratory studies are promising; however, validation studies that demonstrate consistency, reproducibility, and prognostic impact remain uncommon. Prospective clinical trials with standardized procedures are required for clinical translation.

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