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Cardiomyopathies

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Risk Stratification of Left Ventricle Hypertrabeculation Versus Non-Compaction Cardiomyopathy Using Echocardiography, Magnetic Resonance Imaging, and Cardiac Computed Tomography.

Echocardiography (Mount Kisco, N.Y.)
Non-compaction cardiomyopathy (NCCM) is a rare, congenital form of cardiomyopathy characterized by excessive trabeculations in the left ventricle myocardium. NCCM is often an underdiagnosed heart condition characterized by abnormal myocardial trabecu...

Can Generative AI Learn Physiological Waveform Morphologies? A Study on Denoising Intracardiac Signals in Ischemic Cardiomyopathy.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Reducing electrophysiological (EP) signal noise is essential for diagnosis, mapping, and ablation, yet traditional approaches are suboptimal. This study tests the hypothesis that generative artificial intelligence (AI), specifically Variational Autoe...

Detection of cardiac amyloidosis using machine learning on routine echocardiographic measurements.

Open heart
BACKGROUND: Cardiac amyloidosis (CA) is an underdiagnosed, progressive and lethal disease. Machine learning applied to common measurements derived from routine echocardiogram studies can inform suspicion of CA.

Deep learning for cardiac imaging: focus on myocardial diseases, a narrative review.

Hellenic journal of cardiology : HJC = Hellenike kardiologike epitheorese
The integration of computational technologies into cardiology has significantly advanced the diagnosis and management of cardiovascular diseases. Computational cardiology, particularly, through cardiovascular imaging and informatics, enables a precis...

Artificial Intelligence Advancements in Cardiomyopathies: Implications for Diagnosis and Management of Arrhythmogenic Cardiomyopathy.

Current heart failure reports
PURPOSE OF REVIEW: This review aims to explore the emerging potential of artificial intelligence (AI) in refining risk prediction, clinical diagnosis, and treatment stratification for cardiomyopathies, with a specific emphasis on arrhythmogenic cardi...

Pregnancy-Induced Cardiomyopathy: What Case Managers Need to Know.

Professional case management
A new form of stethoscope with artificial intelligence (AI) capabilities may make the difference between early detection of pregnancy-induced cardiomyopathy or end stage postpartum heart failure. The AI stethoscope is a tool that may make that differ...

Artificial intelligence-guided detection of under-recognised cardiomyopathies on point-of-care cardiac ultrasonography: a multicentre study.

The Lancet. Digital health
BACKGROUND: Point-of-care ultrasonography (POCUS) enables cardiac imaging at the bedside and in communities but is limited by abbreviated protocols and variation in quality. We aimed to develop and test artificial intelligence (AI) models to screen f...

Value of Artificial Intelligence for Enhancing Suspicion of Cardiac Amyloidosis Using Electrocardiography and Echocardiography: A Narrative Review.

Journal of the American Heart Association
Nonspecific symptoms and other diagnostic challenges lead to underdiagnosis of cardiac amyloidosis (CA). Artificial intelligence (AI) could help address these challenges, but a summary of the performance of these tools is lacking. This narrative revi...

Deep Learning-based Aligned Strain from Cine Cardiac MRI for Detection of Fibrotic Myocardial Tissue in Patients with Duchenne Muscular Dystrophy.

Radiology. Artificial intelligence
Purpose To develop a deep learning (DL) model that derives aligned strain values from cine (noncontrast) cardiac MRI and evaluate performance of these values to predict myocardial fibrosis in patients with Duchenne muscular dystrophy (DMD). Materials...