systematic review: application of artificial intelligence in breast cancer therapy

Background and objective: gene therapy can be employed to treat several disorders, including cancer. globally, women are more frequently diagnosed with breast cancer than any other cancer type, underscoring the necessity for innovative strategies. algorithms driven by artificial intelligence can enhance the gene therapy process for breast cancer by analyzing vast data sets, identifying intricate patterns, and classifying those patterns. this project aims to perform a literature evaluation focusing on the therapeutic uses of artificial intelligence in gene therapy for breast cancer. materials and methods: for the aim of this study, data was gathered by reading previously published articles and searching the pubmed database for phrases that were relevant to the question being investigated. findings: the ai-driven algorithm analyzes complex molecular pathways in the human body, replicates the knowledge of scientists and physicians in clinical research, and simulates biological processes related to gene regulation, thereby improving the effectiveness of gene vectors, managing gene and drug delivery parameters, and modeling cellular behavior. this method diminishes medical errors and promotes early disease identification and drug efficacy forecasting, thereby providing patients with optimal results from advanced treatments like gene therapy with minimal side effects. conclusion: over the period of the past decade, a multitude of efforts have been made to deploy various gene therapy procedures for breast cancer patients, to achieve the highest possible level of efficacy while minimizing the risk of adverse consequences. as a result, artificial intelligence is considered to be a powerful tool for improving early diagnosis and efficient gene therapy for breast cancer.