Machine learning facilitates the prediction of long-term mortality in patients with tricuspid regurgitation.
Brototo DebChristopher G ScottSorin V PislaruVuyisile T NkomoGarvan Christopher KaneMohamad Adnan AlkhouliJuan A CrestanelloAdelaide Arruda-OlsonPatricia A PellikkaVidhu AnandPublished in: Open heart (2023)
Machine learning of common clinical and echocardiographic features can evaluate mortality risk in patients with TR. Further refinement of models and validation in prospective studies are needed before incorporation into the clinical practice.
Keyphrases
- machine learning
- clinical practice
- aortic valve
- mitral valve
- artificial intelligence
- aortic stenosis
- big data
- ejection fraction
- left ventricular
- cardiovascular events
- transcatheter aortic valve replacement
- pulmonary hypertension
- deep learning
- left atrial
- risk factors
- cardiovascular disease
- type diabetes
- coronary artery disease
- heart failure
- atrial fibrillation