AIMC Topic: Heart Defects, Congenital

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Deep Learning Models for Predicting Left Heart Abnormalities From Single-Lead Electrocardiogram for the Development of Wearable Devices.

Circulation journal : official journal of the Japanese Circulation Society Nov 14, 2023
BACKGROUND: Left heart abnormalities are risk factors for heart failure. However, echocardiography is not always available. Electrocardiograms (ECGs), which are now available from wearable devices, have the potential to detect these abnormalities. Ne...
Humans Electrocardiography Hypertrophy, Left Ventricular Heart Defects, Congenital Echocardiography Deep Learning Wearable Electronic Devices
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A cluster-based ensemble approach for congenital heart disease prediction.

Computer methods and programs in biomedicine Nov 7, 2023
BACKGROUND: One of the most prevalent birth disorders is congenital heart diseases (CHD). Although CHD risk factors have been the subject of numerous studies, their propensity to cause CHD has not been tested. Particularly few research has attempted ...
Random Forest Heart Defects, Congenital Forecasting Cross-Sectional Studies Humans Machine Learning
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Commentary: Is machine learning needed to understand that heart failure is a risk in adult congenital cardiac surgery?

The Journal of thoracic and cardiovascular surgery Oct 14, 2023
Risk Assessment Cardiac Surgical Procedures Heart Failure Heart Defects, Congenital Machine Learning Risk Factors Adult Humans
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Impact of heart failure on reoperation in adult congenital heart disease: An innovative machine learning model.

The Journal of thoracic and cardiovascular surgery Sep 28, 2023
OBJECTIVES: The study objectives were to evaluate the association between preoperative heart failure and reoperative cardiac surgical outcomes in adult congenital heart disease and to develop a risk model for postoperative morbidity/mortality.
Male Middle Aged Risk Assessment Risk Factors Adult Cardiac Surgical Procedures Heart Failure Reoperation Postoperative Complications Time Factors Treatment Outcome Humans Machine Learning Retrospective Studies Female Heart Defects, Congenital
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Fetal electrocardiography and artificial intelligence for prenatal detection of congenital heart disease.

Acta obstetricia et gynecologica Scandinavica Aug 10, 2023
INTRODUCTION: This study aims to investigate non-invasive electrocardiography as a method for the detection of congenital heart disease (CHD) with the help of artificial intelligence.
Fetal Heart Electrocardiography Bayes Theorem Heart Defects, Congenital Infant, Newborn Ultrasonography, Prenatal Humans Artificial Intelligence Pregnancy Female
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Classification of normal and abnormal fetal heart ultrasound images and identification of ventricular septal defects based on deep learning.

Journal of perinatal medicine May 11, 2023
OBJECTIVES: Congenital heart defects (CHDs) are the most common birth defects. Recently, artificial intelligence (AI) was used to assist in CHD diagnosis. No comparison has been made among the various types of algorithms that can assist in the prenat...
Humans Artificial Intelligence Heart Septal Defects, Ventricular Fetal Heart Ultrasonography, Prenatal Pregnancy Female Deep Learning Heart Defects, Congenital
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3D ECG display with deep learning approach for identification of cardiac abnormalities from a variable number of leads.

Physiological measurement Feb 16, 2023
The objective of this study is to explore new imaging techniques with the use of the deep learning method for the identification of cardiac abnormalities present in electrocardiogram (ECG) signals with 2, 3, 4, 6 and 12-lead in the framework of the P...
Electrocardiography Arrhythmias, Cardiac Heart Defects, Congenital Neural Networks, Computer Humans Algorithms Deep Learning
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Application of Artificial Intelligence in Anatomical Structure Recognition of Standard Section of Fetal Heart.

Computational and mathematical methods in medicine Jan 24, 2023
Congenital heart defect (CHD) refers to the overall structural abnormality of the heart or large blood vessels in the chest cavity. It is the most common type of fetal congenital defects. Prenatal diagnosis of congenital heart disease can improve the...
Fetal Heart Humans Echocardiography Ultrasonography, Prenatal Heart Defects, Congenital Artificial Intelligence Pregnancy Female
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Learned iterative segmentation of highly variable anatomy from limited data: Applications to whole heart segmentation for congenital heart disease.

Medical image analysis May 13, 2022
Training deep learning models that segment an image in one step typically requires a large collection of manually annotated images that captures the anatomical variability in a cohort. This poses challenges when anatomical variability is extreme but ...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Thorax Heart Heart Defects, Congenital
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Artificial intelligence in perinatal diagnosis and management of congenital heart disease.

Seminars in perinatology Mar 13, 2022
Prenatal diagnosis and management of congenital heart disease (CHD) has progressed substantially in the past few decades. Fetal echocardiography can accurately detect and diagnose approximately 85% of cardiac anomalies. The prenatal diagnosis of CHD ...
Echocardiography Algorithms Prenatal Diagnosis Humans Heart Defects, Congenital Artificial Intelligence Pregnancy Female
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