Research in biomedicine is generating data on large scales, with more than 100M genomes expected in 2030, electronic health records finally maturing in many countries and standardized imaging of organs or smaller tissues being acquired, digitized and stored in often longitudinal fashion. Preliminary analysis of this data, disease diagnosis and subsequent treatment are often left to human experts who struggle with the volume and complexity of the data. ML can leverage these data sets to diagnose and prevent disease, identify mechanisms and drug targets, and ultimately support clinical decisions.