Multiomics and machine learning in lung cancer prognosis

Abstract

Worldwide, lung cancer accounts for 11.6% of total cancer cases; it is the most common cancer type and the leading cause of cancer death (1). Despite the development of technology and treatment, the prognosis of lung cancer remains poor (2-5). With the development of artificial intelligence technology and the advent of omics, including radiomics, proteomics, genomics, and transcriptomics (6-8), multiomics analysis based on machine learning has great potential to improve lung cancer prognosis. In this paper, schemes based on multiomics and machine learning for improving the prognosis of lung cancer are reviewed.

Topics & Concepts