Research Paper Volume 16, Issue 10 pp 8717—8731

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

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Figure 4. Long-term incidence of developing severity stratified by AI classification using ECG alone. Long-term incidence of developing each moderate-to-severe valvular disease in patients with initially minimal-to-mild valvular diseases stratified by AI classification using ECG alone. Long-term outcome of patients with echocardiographic minimal-to-mild valvular diseases at the time of initial classification, stratified by the initial network classification. The ordinate shows the cumulative incidence of developing moderate-to-severe valvular diseases, and the abscissa indicates years from the time of index ECG–TTE evaluation. A significantly higher risk of future moderate-to-severe valvular diseases was present when the AI algorithm defined the ECG as positive compared with patients with minimal-to-mild valvular diseases who were classified as having a negative finding by the ECG network. The analyses were conducted in both internal and external validation sets. The table shows the at-risk population and cumulative risk for the given time intervals in each risk stratification.