Correlation between artificial intelligence-enabled electrocardiogram and echocardiographic features in aortic stenosis.
Saki ItoMichal Cohen-ShellyItzhak Zachi AttiaEunjung LeePaul A FriedmanVuyisile T NkomoHector I MichelenaPeter A NoseworthyFrancisco Lopez-JimenezJae K OhPublished in: European heart journal. Digital health (2023)
A combination of AS severity, diastolic dysfunction, and LV hypertrophy is reflected in the AI-ECG to detect AS. There seems to be a gradation of the cardiac anatomical/functional features in the model and its identification process of AS is multifactorial.
Keyphrases
- artificial intelligence
- left ventricular
- aortic stenosis
- ejection fraction
- aortic valve replacement
- machine learning
- big data
- transcatheter aortic valve implantation
- deep learning
- transcatheter aortic valve replacement
- left atrial
- heart failure
- mitral valve
- aortic valve
- heart rate variability
- oxidative stress
- heart rate
- pulmonary hypertension
- coronary artery disease
- blood pressure
- atrial fibrillation