Comprehensive clinical application analysis of artificial intelligence-enabled electrocardiograms for screening multiple valvular heart diseases

HIGHLIGHTS

• What: The authors aimed to develop five deep learning models (DLMs) to identify aortic stenosis aortic regurgitation pulmonary regurgitation tricuspid regurgitation and mitral regurgitation. This study has three objectives: (i) to extensively explore the ability of AI-ECG to detect more valvular heart diseases; (ii) to develop a strategy to interpret the AI-ECG results with multiple predictions for further intervention recommendations; and_(iii) to assess the prognostic performance of AI-ECG in individuals without significant valvular heart diseases. The authors only performed prediction once using the best model based on the tuning set in the internal . . .
  

   

  

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