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Artificial intelligence-enhanced electrocardiogram analysis for identifying cardiac autonomic neuropathy in patients with diabetes.

Krzysztof IrlikHanadi AldosariMirela HendelHanna KwiendaczJulia PiaśnikJustyna KulpaPaweł IgnacySylwia BoczekMikołaj HerbaKamil KeglerFrans CoenenJanusz GumprechtYalin ZhengGregory Yoke Hong LipUazman AlamKatarzyna Nabrdalik
Published in: Diabetes, obesity & metabolism (2024)
Our study highlights the potential of using ML techniques, particularly motifs and discords, to effectively detect dsCAN in patients with diabetes. This approach could be applied in large-scale screening of CAN, particularly to identify definite/severe CAN where cardiovascular risk factor modification may be initiated.
Keyphrases
  • artificial intelligence
  • machine learning
  • big data
  • deep learning
  • risk factors
  • left ventricular
  • heart rate variability
  • early onset
  • heart rate
  • blood pressure
  • climate change
  • drug induced
  • data analysis