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Heart Defects, Congenital

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Steroids Improve Hemodynamics in Infants With Adrenal Insufficiency After Cardiac Surgery.

Journal of cardiothoracic and vascular anesthesia
OBJECTIVE: To investigate whether steroid replacement therapy improved hemodynamics in infants after surgery for congenital heart disease only when they develop adrenal insufficiency. The authors retrospectively investigated adrenal function and eval...

Totally robotic repair of atrioventricular septal defect in the adult.

Journal of cardiothoracic surgery
BACKGROUND: Atrioventricular septal defect (AVSD) accounts for up to 3 % of congenital cardiac defects, which is routinely repaired via median sternotomy. Minimally invasive approach such as endoscopic or robotic assisted repair for AVSD has not been...

Identification of Mitral Annulus Hinge Point Based on Local Context Feature and Additive SVM Classifier.

Computational and mathematical methods in medicine
The position of the hinge point of mitral annulus (MA) is important for segmentation, modeling and multimodalities registration of cardiac structures. The main difficulties in identifying the hinge point of MA are the inherent noisy, low resolution o...

Electrocardiogram-based deep learning to predict left ventricular systolic dysfunction in paediatric and adult congenital heart disease in the USA: a multicentre modelling study.

The Lancet. Digital health
BACKGROUND: Left ventricular systolic dysfunction (LVSD) is independently associated with cardiovascular events in patients with congenital heart disease. Although artificial intelligence-enhanced electrocardiogram (AI-ECG) analysis is predictive of ...

Electrocardiogram-based deep learning to predict mortality in paediatric and adult congenital heart disease.

European heart journal
BACKGROUND AND AIMS: Robust and convenient risk stratification of patients with paediatric and adult congenital heart disease (CHD) is lacking. This study aims to address this gap with an artificial intelligence-enhanced electrocardiogram (ECG) tool ...

Machine Learning and Natural Language Processing to Improve Classification of Atrial Septal Defects in Electronic Health Records.

Birth defects research
BACKGROUND: International Classification of Disease (ICD) codes can accurately identify patients with certain congenital heart defects (CHDs). In ICD-defined CHD data sets, the code for secundum atrial septal defect (ASD) is the most common, but it h...

A Generalized Machine Learning Model for Identifying Congenital Heart Defects (CHDs) Using ICD Codes.

Birth defects research
BACKGROUND: International Classification of Diseases (ICD) codes utilized for congenital heart defect (CHD) case identification in datasets have substantial false-positive (FP) rates. Incorporating machine learning (ML) algorithms following case sele...

Deep Learning-Based Electrocardiogram Analysis Predicts Biventricular Dysfunction and Dilation in Congenital Heart Disease.

Journal of the American College of Cardiology
BACKGROUND: Artificial intelligence-enhanced electrocardiogram (AI-ECG) analysis shows promise to detect biventricular pathophysiology. However, AI-ECG analysis remains underexplored in congenital heart disease (CHD).

Data for AI in Congenital Heart Defects: Systematic Review.

Studies in health technology and informatics
Congenital heart disease (CHD) represents a significant challenge in prenatal care due to low prenatal detection rates. Artificial Intelligence (AI) offers promising avenues for precise CHD prediction. In this study we conducted a systematic review a...