AEGAN-Pathifier: a data augmentation method to improve cancer classification for imbalanced gene expression data
AEGAN-Pathifier shows improved performance on the imbalanced datasets GSE25066, GSE20194, BRCA and Liver24. Results from various classifiers indicate that AEGAN-Pathifier has good generalization capability.
Authors
- Jie Hou (ORCID: https://orcid.org/0000-0002-8584-5154)
- Zhaoman Zhong (ORCID: https://orcid.org/0000-0001-8333-6949)
- Qiaosheng Zhang (ORCID: https://orcid.org/0000-0001-6114-8453)
- Hongpeng Li (ORCID: https://orcid.org/0000-0003-0661-7848)
- Yalong Wei
Institutions
- Huzhou Normal University (CN)
- Shanghai Ocean University (CN)
- Ocean University of China (CN)
Publication Details
- Journal
- BMC Bioinformatics
- Published
- 2024-12-26
- DOI
- https://doi.org/10.1186/s12859-024-06013-z
- Citations
- 3
- Primary Topic
- Gene expression and cancer classification
- Type
- article
- Field-Weighted Citation Impact
- 0.70
Funders
- National Natural Science Foundation of China