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Meta-learning reduces the amount of data needed to build AI models in oncology
1Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA, USA. ogevaert@stanford.edu.
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.
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