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Deep neural network for identification of impaired microvascular and vasomotor function from stress electrocardiography.

Jonathan B MoodyAlexis Poitrasson-RivièreJennifer M RenaudTomoe HagioFares AlahdabMouaz H Al MallahMichael D VanderverEdward P FicaroVenkatesh L Murthy
Published in: medRxiv : the preprint server for health sciences (2023)
Signals predictive of microvascular and vasomotor dysfunction are embedded in stress ECG waveforms. These signals can be identified by deep learning methods and are related to prognosis in patients undergoing both stress PET and SPECT MPI.
Keyphrases
  • neural network
  • patients undergoing
  • deep learning
  • pet ct
  • stress induced
  • oxidative stress
  • machine learning
  • heart rate variability
  • heart rate
  • pet imaging