Multi‐modality machine learning approach for risk stratification in heart failure with left ventricular ejection fraction ≤ 45%

AIMS: Heart failure (HF) involves complex remodelling leading to electrical and mechanical dysfunction. We hypothesized that machine learning approaches incorporating data obtained from different investigative modalities including atrial and ventricular measurements from electrocardiography and echo...

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Détails bibliographiques
Publié dans:ESC Heart Fail
Auteurs principaux: Tse, Gary, Zhou, Jiandong, Woo, Samuel Won Dong, Ko, Ching Ho, Lai, Rachel Wing Chuen, Liu, Tong, Liu, Yingzhi, Leung, Keith Sai Kit, Li, Andrew, Lee, Sharen, Li, Ka Hou Christien, Lakhani, Ishan, Zhang, Qingpeng
Format: Artigo
Langue:Inglês
Publié: John Wiley and Sons Inc. 2020
Sujets:
Original Research Articles
Accès en ligne:https://ncbi.nlm.nih.gov/pmc/articles/PMC7754744/
https://ncbi.nlm.nih.gov/pubmed/33094925
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/ehf2.12929
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