Graph Machine Learning For Integrated Multi-omics Analysis

Graph-based workflows and machine learning pipelines are being used to integrate patient information and biomedical knowledge, leading to new discoveries and insights. One study demonstrated the effectiveness of a patient similarity graph-based approach for predicting survival in different types of cancer, while another study showed the potential of integrating genomics and electronic health record data for clinical use. A marginalized graph autoencoder was also found to be effective in stratifying lung cancer patients into distinct subgroups.