A semi-supervised graph convolutional network for early prediction of motor abnormalities in very preterm infants

HIGHLIGHTS

  • who: Hailong Li and collaborators from the Cincinnati, OH, USA Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA have published the research: A Semi-Supervised Graph Convolutional Network for Early Prediction of Motor Abnormalities in Very Preterm Infants, in the Journal: Diagnostics 2023, 1508 of /2023/
  • what: The authors demonstrate the architecture of the developed semi-supervised GCN model in Figure 3. After all of the models were trained, the authors evaluated the model performance by calculating the means and standard deviations (SDs) of five performance metrics, including accuracy, balanced accuracy . . .

     

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