Artificial intelligence techniques in Cancer research: Opportunities and challenges

Abstract

Cancer is a leading cause of mortality and morbidity on a global scale. Cancer research has gradually improved in the past three decades with the advent of automated learning techniques. Artificial Intelligence (AI) practices have emerged as valuable tools in predictive modeling. AI-based prediction models can serve as clinical decision support systems and aid in improving cancer mortality rates. Prominent research works have been conducted to predict cancer at an early stage. AI practices extending from machine learning to deep learning architectures have been employed in cancer prediction. Although the validation of AI prediction models in clinical settings is missing, many studies have still achieved better prediction outcomes than physicians, which advocate integrating AI in real-world settings. The review paper aims to highlight the potential of AI in cancer detection. This study also provides an outline of the automated prediction framework used for the diagnosis of cancer.