Abstract

Info

Title:: Review on application of artificial intelligence in tumor gene expression data analysis

Author(s):: LI Kunpeng; WANG Zepeng; ZHOU Yu; LI Sihai; School of Information Engineering, Gansu University of Chinese Medicine, Lanzhou 730000, China

Keywords:: Keywords: gene expression data artificial intelligence machine learning feature selection review

Abstract:: Abstract: Tumors are serious diseases threatening human health, and the early diagnosis is essential to improve treatment success and patient survival. The study of tumor gene expression data has become a major tool for revealing tumor disease mechanisms, in which artificial intelligence plays an important role. The potential advantages of supervised learning, unsupervised learning and deep learning in tumor prediction and classification are explored from the perspective of machine learning methods. Special attention is paid to the impact of feature selection algorithms on gene screening and their importance in high-dimensional gene expression data. By providing a comprehensive overview of the application and development of artificial intelligence in the analysis of tumor gene expression data, the study aims to provide an outlook for future research directions and promote further development.