Deep centroid: a general deep cascade classifier for biomedical omics data classification.

Journal: Bioinformatics (Oxford, England)
PMID: 38305432

Abstract

MOTIVATION: Classification of samples using biomedical omics data is a widely used method in biomedical research. However, these datasets often possess challenging characteristics, including high dimensionality, limited sample sizes, and inherent biases across diverse sources. These factors limit the performance of traditional machine learning models, particularly when applied to independent datasets.

Authors

  • Kuan Xie
    Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, People's Republic of China.
  • Yuying Hou
    Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, People's Republic of China.
  • Xionghui Zhou
    Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, People's Republic of China.

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