MMDAE-HGSOC: A novel method for high-grade serous ovarian cancer molecular subtypes classification based on multi-modal deep autoencoder

Hui-Qing Wang, Hao-lin Li, Jia-Le Han, Zhi Peng Feng, Hong-Xia Deng, Xiao Han. MMDAE-HGSOC: A novel method for high-grade serous ovarian cancer molecular subtypes classification based on multi-modal deep autoencoder. Computers & Chemistry, 105:107906, August 2023. [doi]

@article{WangLHFDH23,
  title = {MMDAE-HGSOC: A novel method for high-grade serous ovarian cancer molecular subtypes classification based on multi-modal deep autoencoder},
  author = {Hui-Qing Wang and Hao-lin Li and Jia-Le Han and Zhi Peng Feng and Hong-Xia Deng and Xiao Han},
  year = {2023},
  month = {August},
  doi = {10.1016/j.compbiolchem.2023.107906},
  url = {https://doi.org/10.1016/j.compbiolchem.2023.107906},
  researchr = {https://researchr.org/publication/WangLHFDH23},
  cites = {0},
  citedby = {0},
  journal = {Computers & Chemistry},
  volume = {105},
  pages = {107906},
}