Editorial
Copyright ©The Author(s) 2020.
Artif Intell Cancer. Jun 28, 2020; 1(1): 1-7
Published online Jun 28, 2020. doi: 10.35713/aic.v1.i1.1
Figure 1
Figure 1 Artificial intelligence and omics to improve the management of patients with cancer. Actual artificial intelligence algorithms are mainly fueled with clinical data (e.g. clinical records, computed tomography scan, magnetic resonance imaging) and omics data, as exemplified by those from The Cancer Genome Atlas consortium (e.g. genetic, epigenetic, transcriptomic, proteomic, metabolomics profiles). They pave the way for future models that will integrate personalized clinical information related to lifestyle of each patient, including exposome and microbiome, in order to improve cancer diagnosis, prognosis prediction and treatment efficacy. AI: Artificial intelligence; TCGA: The Cancer Genome Atlas.