Application of CRISPR combined with deep learning in cancer detection and therapy

Abstract. Cancer is a huge health issue around the world, and genetic abnormalities are one of the leading causes. Gene editing has gained importance in cancer research with the advent of CRISPR technology, particularly the CRISPR/Cas system, which is utilized in cancer detection and treatment because of its high specificity and sensitivity. Meanwhile, as a branch of machine learning, deep learning has shown great potential in cancer detection and treatment by constructing and training multi-layer neural networks. Deep learning algorithms increase the accuracy of early cancer diagnosis by detecting gene mutations and expression patterns linked to cancer. This article reviews the most recent applications of CRISPR combined with deep learning in cancer detection and treatment. CRISPR technology has shown outstanding performance in nucleic acid testing, virus detection, and protein detection; In terms of treatment, it can be utilized to remove cancer-related genes by gene editing , enhance immune cell function, and improve the efficiency of immunotherapy. Deep learning techniques play an important role in cancer diagnosis, prognosis prediction, and CRISPR targeted and off target prediction. Combining CRISPR and deep learning is expected to improve cancer detection and treatment methods, providing new directions for future research.