Meta-learning reduces the amount of data needed to build AI models in oncology

Abstract

Meta-learning is showing promise in recent genomic studies in oncology. Meta-learning can facilitate transfer learning and reduce the amount of data that is needed in a target domain by transferring knowledge from abundant genomic data in different source domains enabling the use of AI in data scarce scenarios.