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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...

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Detalles Bibliográficos
Autores principales: Shen, Wan Xiang, Liu, Yu, Chen, Yan, Zeng, Xian, Tan, Ying, Jiang, Yu Yang, Chen, Yu Zong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
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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