The prognostic value of artificial intelligence to predict cardiac amyloidosis in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement.
Milagros Pereyra PietriJuan M FarinaAhmed K MahmoudIsabel G ScaliaFrancesca GalassoMichael E KillianMustafa SuppahCourtney R KenyonLaura M KoepkeRatnasari PadangChieh-Ju ChaoJohn P SweeneyF David FortuinMackram F EleidKristen A Sell-DottinDavid E SteidleyLuis R ScottRafael FonsecaFrancisco Lopez-JimenezZachi I AttiaAngela DispenzieriMartha GroganJulie L RosenthalReza ArsanjaniChadi AyoubPublished in: European heart journal. Digital health (2024)
Artificial intelligence applied to pre-TAVR ECGs identifies a subgroup at higher risk of clinical events. These targeted patients may benefit from further diagnostic evaluation for CA.
Keyphrases
- artificial intelligence
- aortic stenosis
- transcatheter aortic valve replacement
- ejection fraction
- aortic valve
- aortic valve replacement
- machine learning
- big data
- transcatheter aortic valve implantation
- deep learning
- left ventricular
- end stage renal disease
- chronic kidney disease
- heart failure
- newly diagnosed
- coronary artery disease
- early onset
- genome wide
- randomized controlled trial
- drug delivery
- prognostic factors
- dna methylation
- clinical trial
- study protocol