| Literature DB >> 32735452 |
Tricia Chinnery1, Andrew Arifin2, Keng Yeow Tay3, Andrew Leung3, Anthony C Nichols4, David A Palma2, Sarah A Mattonen1,2, Pencilla Lang2.
Abstract
Artificial 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.Entities:
Keywords: artificial intelligence; head and neck cancer; machine learning; predictive modeling; radiomics
Year: 2020 PMID: 32735452 DOI: 10.1177/0846537120942134
Source DB: PubMed Journal: Can Assoc Radiol J ISSN: 0846-5371 Impact factor: 2.248