Identifying high-risk Fontan phenotypes using K-means clustering of cardiac magnetic resonance-based dyssynchrony metrics

Background: Individuals with a Fontan circulation encompass a heterogeneous group with adverse outcomes linked to ventricular dilation, dysfunction, and dyssynchrony. The purpose of this study was to assess if unsupervised machine learning cluster analysis of cardiovascular magnetic resonance (CMR)-...

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Detaylı Bibliyografya
Asıl Yazarlar:	Addison Gearhart, Sunakshi Bassi, Rahul H. Rathod, Rebecca S. Beroukhim, Stuart Lipsitz, Maxwell P. Gold, David M. Harrild, Audrey Dionne, Sunil J. Ghelani
Materyal Türü:	Artigo
Dil:	Inglês
Baskı/Yayın Bilgisi:	Elsevier 2024-01-01
Seri Bilgileri:	Journal of Cardiovascular Magnetic Resonance
Konular:	Unsupervised machine learning Pediatrics Fontan Cardiovascular magnetic resonance imaging Dyssynchrony
Online Erişim:	http://www.sciencedirect.com/science/article/pii/S1097664724010871
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Identifying high-risk Fontan phenotypes using K-means clustering of cardiac magnetic resonance-based dyssynchrony metrics

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