Heart failure with preserved ejection fraction phenogroup classification using machine learning.
Atsushi KyodoKoshiro KanaokaAyaka KeshiMaki NogiKazutaka NogiSatomi IshiharaDaisuke KamonYukihiro HashimotoYasuki NakadaTomoya UedaAyako SenoTaku NishidaKenji OnoueTsuneari SoedaRika KawakamiMakoto WatanabeToshiyuki NagaiToshihisa AnzaiYoshihiko SaitoPublished in: ESC heart failure (2023)
ML could successfully stratify Japanese HFpEF patients into three phenogroups (atherosclerosis and chronic kidney disease, atrial fibrillation, and younger and left ventricular hypertrophy groups).
Keyphrases
- end stage renal disease
- chronic kidney disease
- left ventricular
- peritoneal dialysis
- atrial fibrillation
- heart failure
- newly diagnosed
- left atrial
- cardiovascular disease
- ejection fraction
- prognostic factors
- deep learning
- coronary artery disease
- acute myocardial infarction
- hypertrophic cardiomyopathy
- patient reported
- aortic stenosis
- mitral valve