Cancer is a major medical problem worldwide. Due to its high heterogeneity, the use of the same drugs or surgical methods in patients with the same
tumor may have different curative effects, leading to the need for more accurate treatment methods for
tumors and personalized treatments for patients. The precise treatment of
tumors is essential, which renders obtaining an in-depth understanding of the changes that
tumors undergo urgent, including changes in their genes,
proteins and
cancer cell phenotypes, in order to develop targeted treatment strategies for patients. Artificial intelligence (AI) based on big data can extract the hidden patterns, important information, and corresponding knowledge behind the enormous amount of data. For example, the ML and deep learning of subsets of AI can be used to mine the deep-level information in genomics, transcriptomics, proteomics, radiomics, digital pathological images, and other data, which can make clinicians synthetically and comprehensively understand
tumors. In addition, AI can find new
biomarkers from data to assist
tumor screening, detection, diagnosis, treatment and prognosis prediction, so as to providing the best treatment for individual patients and improving their clinical outcomes.