ABSTRACT:
Over the past decade, artificial intelligence (AI) has played a significant role in solving a number of medical issues, including cancer. One area of IA that stands out is deep learning (DL), which is distinguished by its ability to do automatic feature extraction and has significant strength in processing and analyzing large amounts of complex data. Thanks to a wealth of medical data and cutting-edge computer technologies, IA—particularly deep learning—has found use in various areas of cancer research and holds promise for enhancing cancer diagnosis and treatment.
These applications cover a wide range, including early cancer detection, diagnostics, classification and grading, molecular tumor characterization, anticipating treatment outcomes and patient reactions, developing a customized treatment plan, automating radiotherapy workflow, developing novel anti-cancer medications, and preliminary clinical trials. In this review, we introduced the general idea behind IA, outlined the primary areas in which it is used to diagnose and treat cancer, and discussed its future prospects as well as its ongoing challenges. By increasing the use of IA in clinical settings, we can anticipate the emergence of cancer treatments driven by artificial intelligence.
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