AIMC Topic: Echocardiography

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Utility of an Echocardiographic Machine Learning Model to Predict Outcomes in Intensive Cardiac Care Unit Patients.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography Dec 14, 2024
INTRODUCTION: The risk stratification at admission to the intensive cardiac care unit (ICCU) is crucial and remains challenging.
Echocardiography Humans Middle Aged Prognosis Risk Assessment Intensive Care Units Female Machine Learning Aged Prospective Studies Male Hospital Mortality Coronary Care Units
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Deep learning for cardiac imaging: focus on myocardial diseases, a narrative review.

Hellenic journal of cardiology : HJC = Hellenike kardiologike epitheorese Dec 9, 2024
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...
Echocardiography Deep Learning Cardiomyopathies Cardiac Imaging Techniques Humans
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BEAS-Net: A Shape-Prior-Based Deep Convolutional Neural Network for Robust Left Ventricular Segmentation in 2-D Echocardiography.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Nov 27, 2024
Left ventricle (LV) segmentation of 2-D echocardiography images is an essential step in the analysis of cardiac morphology and function and-more generally-diagnosis of cardiovascular diseases (CVD). Several deep learning (DL) algorithms have recently...
Image Processing, Computer-Assisted Heart Ventricles Echocardiography Deep Learning Convolutional Neural Networks Neural Networks, Computer Algorithms Humans
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Hardware-Independent Deep Signal Processing: A Feasibility Study in Echocardiography.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Nov 27, 2024
Deep learning (DL) models have emerged as alternative methods to conventional ultrasound (US) signal processing, offering the potential to mimic signal processing chains, reduce inference time, and enable the portability of processing chains across h...
Humans Image Processing, Computer-Assisted Signal Processing, Computer-Assisted Heart Feasibility Studies Algorithms Echocardiography Deep Learning
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Spatiotemporal Deep Learning-Based Cine Loop Quality Filter for Handheld Point-of-Care Echocardiography.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Nov 27, 2024
The reliability of automated image interpretation of point-of-care (POC) echocardiography scans depends on the quality of the acquired ultrasound data. This work reports on the development and validation of spatiotemporal deep learning models to asse...
Heart Ventricles Image Interpretation, Computer-Assisted Point-of-Care Systems Echocardiography Humans Deep Learning Algorithms Reproducibility of Results
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Extraction and evaluation of features of preterm patent ductus arteriosus in chest X-ray images using deep learning.

Scientific reports Nov 26, 2024
Echocardiography is the gold standard of diagnosis and evaluation of patent ductus arteriosus (PDA), a common condition among preterm infants that can cause hemodynamic abnormalities and increased mortality rates, but this technique requires a skille...
Infant, Premature Radiography, Thoracic Humans Ductus Arteriosus, Patent Male Intensive Care Units, Neonatal Female Echocardiography Infant, Newborn Deep Learning
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Machine Learning Identifies Clinically Distinct Phenotypes in Patients With Aortic Regurgitation.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography Nov 18, 2024
BACKGROUND: Aortic regurgitation (AR) is a prevalent valve disease with a long latent period before symptoms appear. Recent data has suggested the role of novel markers of myocardial overload in assessing onset of decompensation.
Survival Rate Male Echocardiography Retrospective Studies Female Aged Machine Learning Middle Aged Phenotype Humans Severity of Illness Index Aortic Valve Insufficiency
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A deep learning based method for left ventricular strain measurements: repeatability and accuracy compared to experienced echocardiographers.

BMC medical imaging Nov 12, 2024
BACKGROUND: Speckle tracking echocardiography (STE) provides quantification of left ventricular (LV) deformation and is useful in the assessment of LV function. STE is increasingly being used clinically, and every effort to simplify and standardize S...
Heart Ventricles Echocardiography Humans Middle Aged Adult Female Deep Learning Male Reproducibility of Results Ventricular Function, Left Aged
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Precision of artificial intelligence in paediatric cardiology multimodal image interpretation.

Cardiology in the young Nov 11, 2024
Multimodal imaging is crucial for diagnosis and treatment in paediatric cardiology. However, the proficiency of artificial intelligence chatbots, like ChatGPT-4, in interpreting these images has not been assessed. This cross-sectional study evaluates...
Humans Artificial Intelligence Clinical Competence Child Cross-Sectional Studies Echocardiography Electrocardiography Multimodal Imaging Image Interpretation, Computer-Assisted Pediatrics Cardiology
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Detection of Right and Left Ventricular Dysfunction in Pediatric Patients Using Artificial Intelligence-Enabled ECGs.

Journal of the American Heart Association Nov 4, 2024
BACKGROUND: Early detection of left and right ventricular systolic dysfunction (LVSD and RVSD respectively) in children can lead to intervention to reduce morbidity and death. Existing artificial intelligence algorithms can identify LVSD and RVSD in ...
Predictive Value of Tests Ventricular Dysfunction, Right Ventricular Dysfunction, Left Ventricular Function, Right Child, Preschool Child Electrocardiography Echocardiography Infant Adolescent Artificial Intelligence Algorithms Retrospective Studies Ventricular Function, Left Stroke Volume Female Humans Male
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