YUHAN JI1, YONG LIANG1,*, ZIYI YANG2, NING AI1
BIOCELL, Vol.47, No.3, pp. 569-579, 2023, DOI:10.32604/biocell.2023.025865
Abstract Few-shot learning is becoming more and more popular in many fields, especially in the computer vision field. This inspires us to introduce few-shot learning to the genomic field, which faces a typical few-shot problem because some tasks only have a limited number of samples with high-dimensions. The goal of this study was to investigate the few-shot disease sub-type prediction problem and identify patient subgroups through training on small data. Accurate disease sub-type classification allows clinicians to efficiently deliver investigations and interventions in clinical practice. We propose the SW-Net, which simulates the clinical process of extracting the shared knowledge from a… More >
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