Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

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

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance - 1 Jan 2000

Gearhart Addison, Bassi Sunakshi, Rathod Rahul H, Beroukhim Rebecca S, Lipsitz Stuart, Gold Maxwell P, Harrild David M, Dionne Audrey, Ghelani Sunil J

Abstract excerpt

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)-derived dyssynchrony metrics can separate ventricles in the Fontan circulation from normal control left ventricles...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Biomechanical Phenomena
Share to Heart Transplantation

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Image Interpretation, Computer-Assisted

Share to Magnetic Resonance Imaging, Cine

Share to Myocardial Contraction

Share to Unsupervised Machine Learning

Share to Ventricular Dysfunction, Left

Share to Ventricular Function, Left

Source

Open in PubMed Open full text

Identifiers

PMID: 39004418
DOI: 10.1016/j.jocmr.2024.101060
PMCID: PMC11347047

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 2 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Identifying high-risk Fontan phenotypes using K-means clustering of cardiac magnetic resonance-based dyssynchrony metrics.PMID 39004418Read ↗

Unsupervised phenotype clustering of non-ischemic dilated cardiomyopathy with AI-assisted T1 mapping cardiac MRSemantic proximity Read ↗

Unsupervised clustering of intra-ventricular haemodynamic forces for the phenotyping of left ventricular function in non-ischaemic left ventricular cardiomyopathy.Semantic proximity Read ↗

Phenotyping of Mitral Valve Prolapse Without Severe Mitral Regurgitation Using Electrocardiographic and Echocardiographic Data.Semantic proximity Read ↗

Unsupervised phenotypic clustering of cardiac MRI data reveals distinct subgroups associated with outcomes in ischemic cardiomyopathy.Semantic proximity Read ↗

Arrhythmic Mitral Valve Prolapse Phenotype: An Unsupervised Machine Learning Analysis Using a Multicenter Cardiac MRI Registry.Semantic proximity Read ↗

Machine Learning Identification of Patient Phenoclusters in Aortic Regurgitation.Semantic proximity Read ↗

Phenotypic clustering analysis of patients rejected for mitral valve interventions: implications for future transcatheter technologies.Semantic proximity Read ↗

Phenotypic Clustering of Left Ventricular Diastolic Function Parameters: Patterns and Prognostic Relevance.Semantic proximity Read ↗

Clinical phenotypes among patients that underwent cardiac resynchronization therapy using unsupervised learning integrating gated SPECT.Semantic proximity Read ↗

Functional tricuspid regurgitation: A clustering analysis and prognostic validation of three echocardiographic phenotypes in an external cohort.Semantic proximity Read ↗

Advanced hemodynamic and cluster analysis for identifying novel RV function subphenotypes in patients with pulmonary hypertension.Semantic proximity Read ↗

Clinical and prognostic implications of phenomapping in patients with heart failure receiving cardiac resynchronization therapy.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.