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AggMapNet: enhanced and explainable low-sample omics deep learning with feature-aggregated multi-channel networks
Omics-based biomedical learning frequently relies on data of high-dimensions (up to thousands) and low-sample sizes (dozens to hundreds), which challenges efficient deep learning (DL) algorithms, particularly for low-sample omics investigations. Here, an unsupervised novel feature aggregation tool A...
Autores principales: | Shen, Wan Xiang, Liu, Yu, Chen, Yan, Zeng, Xian, Tan, Ying, Jiang, Yu Yang, Chen, Yu Zong |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9071488/ https://www.ncbi.nlm.nih.gov/pubmed/35100418 http://dx.doi.org/10.1093/nar/gkac010 |
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