Review of recent impacts of artificial intelligence for radiation therapy procedures

Abstract

Artificial intelligence (AI) is a discipline of computing science whose goal is to develop intelligent computer-based systems replicating humans' decision-making and problem-solving abilities. Globally, 26 million new cancer cases are expected to be diagnosed in 2030, with cancer death accounting for nearly half of the incidence. The challenge in radiation therapy is increasing tumor control probability while minimizing damage to surrounding normal tissue. The objective of this review study is to review the recent developments in the use of AI for radiation therapy and dose optimization. The current study examines recent research publications published in the last ten years on the Web of Science, Scopus, and PubMed databases related to AI. The study revealed that AI is valuable, helps improve radiotherapy outcomes, and allows for the processing and analysis of enormous datasets. AI enables the iterative implementation of complicated functions in massive data files (e.g., defining healthy tissue or determining ideal treatment planning) for image segmentation and outcome prediction, benefiting the entire radiation therapy community.