Background and Aims: Artificial intelligence has been an active research topic in recent years and has contributed to the resolution of a variety of medical problems, including cancer. Artificial intelligence is revolutionizing
cancer research and treatment using advanced methods. This systematic review was conducted to investigate the role of
artificial intelligence in
cancer research. Methods: A systematic and comprehensive search for studies published between ۲۰۱۹ and ۲۰۲۴ was conducted in databases such as PubMed, Scopus, EMBASE, Web of Science, and the Cochrane Library, using keywords such as “cancer,” “artificial intelligence,” and “cancer research.” Studies were selected based on predefined inclusion and exclusion criteria. The inclusion criteria included studies that dealt with the application of
artificial intelligence in at least one of the fields of
cancer diagnosis, prevention, or treatment. Duplicates, non-English language studies, and articles with unavailable full text were excluded. The remaining studies were reviewed by two researchers; their abstracts were examined, and low-quality or unrelated studies were excluded. A risk of bias assessment was conducted using the JBI tool, which includes evaluation methodologies for all types of studies. The selected studies were critically appraised, and relevant data were extracted. This review followed the PRISMA statement. Results: Out of ۱۸۵ articles, ۱۷ articles were included in this systematic review. These studies demonstrated the diverse applications of Artificial intelligence in
cancer research, encompassing discovery of drugs, early detection and staging of cancer, detecting
cancer mutations using machine learning, predicting drug efficacy, prognosis prediction, imaging analysis, patient matching for clinical trials, biomarker and genetics analysis, and the role of Artificial intelligence in improving patient care and clinical decision-making. This tools can help pathologists in diagnosing
cancer more accurately and consistently, reducing the case error rates, estimate the likelihood for a person to get
cancer by identifying the risk factors. Conclusion: This systematic review highlights the promising role of Artificial intelligence in
cancer research, emphasizing opportunities for early detection, enhancing treatment strategies, and understanding disease mechanisms. However, further integration
