Results 151 to 160 of about 256,093 (311)

Impact of genotype–phenotype associations on prognosis in dilated cardiomyopathy

open access: yesEuropean Journal of Heart Failure, EarlyView.
Prediction of clinical outcomes in genetic dilated cardiomyopathy (DCM). LVEF, left ventricular ejection fraction. Aims Dilated cardiomyopathy (DCM) has a monogenic aetiology in up to 40% of patients. Understanding the spectrum of genotype–phenotype associations in DCM is crucial for risk stratification and personalized treatment.
Sophie L.V.M. Stroeks   +27 more
wiley   +1 more source

Safety of Heart Rate Control and Relationship to Radiation Exposure from Coronary CT Angiography in 4,171 Studies [PDF]

open access: bronze, 2012
Christian Hamilton‐Craig   +5 more
openalex   +1 more source

Arrhythmogenic cardiomyopathy mimicking cardiac amyloidosis with Waldenström macroglobulinaemia: A diagnostic challenge

open access: yes
ESC Heart Failure, EarlyView.
Lianyue Ma   +7 more
wiley   +1 more source

Metabolic Signatures and Diagnostic Prediction Models for Coronary Artery Disease and Type 2 Diabetes Mellitus: Insights From an Exploratory Study

open access: yesiNew Medicine, EarlyView.
Metabolomic & lipidomic analysis reveals metabolic overlap between CAD & T2DM, highlighting 7 key metabolites as potential biomarkers. A predictive model based on these achieves high accuracy, potentially advancing precision medicine & metabolic insights.
Zhihua Wang   +9 more
wiley   +1 more source

Diagnostic accuracy of coronary CT angiography performed with a novel whole heart coverage high-definition CT scanner in atrial fibrillation patients

open access: green, 2017
Daniele Andreini   +8 more
openalex   +1 more source

Heart Rate-Dependent Degree of Motion Artifacts in Coronary CT Angiography Acquired by a Novel Purpose-Built Cardiac CT Scanner [PDF]

open access: gold, 2022
Milán Vecsey-Nagy   +13 more
openalex   +1 more source

Exploring a Novel Conv‐Transformer Network for Multi‐Modality Heart Segmentation

open access: yesiRADIOLOGY, EarlyView.
We propose SFAM‐TransUnet for multimodality whole heart segmentation, a novel deep learning framework combining CNNs and transformers. Extensive experiments conducted on the clinical Multi‐Modality Whole Heart Segmentation datasets demonstrate that SFAM‐TransUnet outperforms various alternative methods.
Youyou Ding   +6 more
wiley   +1 more source

Drug Eluting Stents & Coronary Angiography

open access: diamond, 2006
Bharat Rawat, PR Poudel, Smriti Mulmi
openalex   +2 more sources

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