Deep learning to assess right ventricular ejection fraction from two-dimensional echocardiograms in precapillary pulmonary hypertension.
Michito MurayamaHiroyuki SugimoriTakaaki YoshimuraSanae KagaHideki ShimaSatonori TsunetaAoi MukaiYui NagaiShinobu YokoyamaHisao NishinoJunichi NakamuraTakahiro SatoIchizo TsujinoPublished in: Echocardiography (Mount Kisco, N.Y.) (2024)
The fully automated DL-based tool using 2D echocardiography could accurately estimate RVEF and exhibited a diagnostic performance for RV systolic dysfunction comparable to that of human readers.
Keyphrases
- pulmonary hypertension
- ejection fraction
- deep learning
- aortic stenosis
- pulmonary artery
- left ventricular
- pulmonary arterial hypertension
- endothelial cells
- mycobacterium tuberculosis
- machine learning
- blood pressure
- artificial intelligence
- heart failure
- convolutional neural network
- oxidative stress
- induced pluripotent stem cells
- high throughput
- computed tomography
- transcatheter aortic valve replacement
- coronary artery
- coronary artery disease
- aortic valve