Abstract

Cancer is a disorder with aggressive, low-median survival. Unfortunately, the healing time is long and expensive owing to high recurrence and mortality rates. It is essential to increase patient survival. Over the years, mathematical and computer engineering advancements have inspired numerous scientists to use quantitative methods to evaluate disease prognosis, such as multivariate statistical analysis, and the precision of these studies is considerably higher than that of observational predictions. However, as artificial intelligence (AI) has found widespread applications in clinical cancer research in recent years, especially machine learning and deep learning, cancer prediction output has reached new heights. The literature on the use of AI for cancer diagnosis and prognosis is discussed in this part. We discuss how AI supports the diagnosis of cancer, especially in terms of its unparalleled precision. We also illustrate forms in which these approaches progress the field. Opportunities and problems are addressed in the clinical application of AI.