Clinical Application of Artificial Intelligence in Cancer Treatment: A Systematic Literature Review

Abstract

Context: Artificial intelligence (AI) has emerged as a promising tool for improving cancer diagnosis, treatment, and patient outcomes in recent years. Evidence Acquisition: This systematic literature review explores AI's potential role in cancer therapeutics. PubMed, Scopus, and Web of Science databases were searched using the keywords “artificial intelligence,” AI, “machine learning,” cancer, neoplasms, therapy, and therapeutic from October to December 2023. Original English articles that focused on the use of AI in cancer treatment and whose full texts were available were included in the present study. Finally, 24 articles met the inclusion criteria for the present study. Results: The analysis of the included articles showed that the role of AI in cancer treatment has been focused on three areas: Predicting treatment response, precision medicine, and predicting cancer treatment adverse events. The present review also identifies challenges and limitations in the implementation of AI in cancer therapeutics, such as issues related to data collection, data analysis, and the quality of data. Conclusions: The integration of AI in cancer care necessitates a strong health policy infrastructure. This infrastructure must prioritize ethical concerns such as confidentiality of information, neutrality of algorithms, and access, in addition to responsible AI development, transparency, and patient safety. Overall, this review provides critical insights into the current state of AI in the clinical settings of cancer treatment.