MuscNet, a Weighted Voting Model of Multi-Source Connectivity Networks to Predict Mild Cognitive Impairment Using Resting-State Functional MRI

Jialiang Li, Zhaomin Yao, Meiyu Duan, Shuai Liu 0010, Fei Li, Haiyang Zhu, Zhiqiang Xia, Lan Huang 0002, Fengfeng Zhou. MuscNet, a Weighted Voting Model of Multi-Source Connectivity Networks to Predict Mild Cognitive Impairment Using Resting-State Functional MRI. IEEE Access, 8:174023-174031, 2020. [doi]

@article{LiYDLLZXHZ20,
  title = {MuscNet, a Weighted Voting Model of Multi-Source Connectivity Networks to Predict Mild Cognitive Impairment Using Resting-State Functional MRI},
  author = {Jialiang Li and Zhaomin Yao and Meiyu Duan and Shuai Liu 0010 and Fei Li and Haiyang Zhu and Zhiqiang Xia and Lan Huang 0002 and Fengfeng Zhou},
  year = {2020},
  doi = {10.1109/ACCESS.2020.3025828},
  url = {https://doi.org/10.1109/ACCESS.2020.3025828},
  researchr = {https://researchr.org/publication/LiYDLLZXHZ20},
  cites = {0},
  citedby = {0},
  journal = {IEEE Access},
  volume = {8},
  pages = {174023-174031},
}