The field of oncology is changing drastically as a result of monumental advancements in artificial intelligence (AI), providing new and significant prospects to enhance patient care. These developments enable researchers and clinicians to incorporate and synthesize an expanding collection of diverse patient information, identify trends, and forecast outcomes to enhance collaborative decision-making to improve cancer care. An increasingly wide range of scientific and therapeutic studies on cancer applications are making use of deep learning, a highly versatile subfield of AI that facilitates autonomous extraction of features. From this vantage point, oncologists should stay current with the various studies and perspectives that have examined and implemented various clinical cancer treatment touchpoints for narrow-task AI applications, outline the difficulties encountered in the clinical use of AI, and recommend future directions for integrating AI into customized care for patients, with a focus on accessibility, clinical validity, and usefulness. In this review, we provide an overview of the recent seminal works on the application of AI in oncology.
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