Deep learning based fetal distress detection from time frequency representation of cardiotocogram signal using morse wavelet: research study

HIGHLIGHTS

• who: Yared Daniel Daydulo from the School of Biomedical Engineering, Institute of Technology have published the paper: Deep learning based fetal distress detection from time frequency representation of cardiotocogram signal using Morse wavelet: research study, in the Journal: (JOURNAL)
• what: In this study an innovative computer aided fetal distress diagnosing model is developed by using time frequency representation of FHR signal using generalized Morse wavelet and the concept of transfer learning of pre-trained ResNet 50 deep neural network model. Main outcome measures: Sensitivity (Se) specificity (Sp) and accuracy (Acc) of the model adopted from . . .
  

   

  

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