AIMC Topic: Heart Defects, Congenital

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Identifying high-risk Fontan phenotypes using K-means clustering of cardiac magnetic resonance-based dyssynchrony metrics.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Jul 14, 2024
BACKGROUND: Individuals with a Fontan circulation encompass a heterogeneous group with adverse outcomes linked to ventricular dilation, dysfunction, and dyssynchrony. The purpose of this study was to assess if unsupervised machine learning cluster an...
Ventricular Dysfunction, Left Image Interpretation, Computer-Assisted Heart Transplantation Biomechanical Phenomena Fontan Procedure Male Ventricular Function, Left Female Cluster Analysis Risk Assessment Risk Factors Heart Defects, Congenital Adolescent Young Adult Unsupervised Machine Learning Time Factors Adult Predictive Value of Tests Child Magnetic Resonance Imaging, Cine Treatment Outcome Myocardial Contraction Humans Phenotype Retrospective Studies
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A Coarse-Fine Collaborative Learning Model for Three Vessel Segmentation in Fetal Cardiac Ultrasound Images.

IEEE journal of biomedical and health informatics Jul 2, 2024
Congenital heart disease (CHD) is the most frequent birth defect and a leading cause of infant mortality, emphasizing the crucial need for its early diagnosis. Ultrasound is the primary imaging modality for prenatal CHD screening. As a complement to ...
Humans Algorithms Aorta Pregnancy Ultrasonography, Prenatal Female Pulmonary Artery Deep Learning Fetal Heart Image Interpretation, Computer-Assisted Vena Cava, Superior Heart Defects, Congenital
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Machine Learning-Based Critical Congenital Heart Disease Screening Using Dual-Site Pulse Oximetry Measurements.

Journal of the American Heart Association Jun 15, 2024
BACKGROUND: Oxygen saturation (Spo) screening has not led to earlier detection of critical congenital heart disease (CCHD). Adding pulse oximetry features (ie, perfusion data and radiofemoral pulse delay) may improve CCHD detection, especially coarct...
Neonatal Screening Heart Defects, Congenital Oximetry Algorithms Prospective Studies Female Male Humans ROC Curve Infant, Newborn Machine Learning Predictive Value of Tests Oxygen Saturation
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Investigation on ultrasound images for detection of fetal congenital heart defects.

Biomedical physics & engineering express May 31, 2024
Congenital heart defects (CHD) are one of the serious problems that arise during pregnancy. Early CHD detection reduces death rates and morbidity but is hampered by the relatively low detection rates (i.e., 60%) of current screening technology. The d...
Humans Neural Networks, Computer Algorithms Heart Defects, Congenital Pregnancy Fetal Heart Ultrasonography, Prenatal Female Deep Learning Echocardiography Image Processing, Computer-Assisted Fetus
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Heart and great vessels segmentation in congenital heart disease via CNN and conditioned energy function postprocessing.

International journal of computer assisted radiology and surgery May 30, 2024
PURPOSE: The segmentation of the heart and great vessels in CT images of congenital heart disease (CHD) is critical for the clinical assessment of cardiac anomalies and the diagnosis of CHD. However, the diverse types and abnormalities inherent in CH...
Imaging, Three-Dimensional Heart Heart Defects, Congenital Aorta Pulmonary Artery Humans Neural Networks, Computer Tomography, X-Ray Computed
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Art or Artifact: Evaluating the Accuracy, Appeal, and Educational Value of AI-Generated Imagery in DALL·E 3 for Illustrating Congenital Heart Diseases.

Journal of medical systems May 23, 2024
Artificial Intelligence (AI), particularly AI-Generated Imagery, has the potential to impact medical and patient education. This research explores the use of AI-generated imagery, from text-to-images, in medical education, focusing on congenital hear...
Humans Heart Defects, Congenital Artificial Intelligence
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Machine Learning Quantification of Pulmonary Regurgitation Fraction from Echocardiography.

Pediatric cardiology May 10, 2024
Assessment of pulmonary regurgitation (PR) guides treatment for patients with congenital heart disease. Quantitative assessment of PR fraction (PRF) by echocardiography is limited. Cardiac MRI (cMRI) is the reference-standard for PRF quantification. ...
Adolescent Child, Preschool Child ROC Curve Heart Defects, Congenital Magnetic Resonance Imaging, Cine Pulmonary Valve Insufficiency Retrospective Studies Adult Female Male Young Adult Echocardiography Infant Humans Machine Learning Algorithms
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Machine Learning to Predict Outcomes of Fetal Cardiac Disease: A Pilot Study.

Pediatric cardiology May 9, 2024
Prediction of outcomes following a prenatal diagnosis of congenital heart disease (CHD) is challenging. Machine learning (ML) algorithms may be used to reduce clinical uncertainty and improve prognostic accuracy. We performed a pilot study to train M...
Female Infant, Newborn Ultrasonography, Prenatal Pilot Projects Machine Learning Prognosis Pregnancy Fetal Diseases Heart Defects, Congenital Prenatal Diagnosis Humans
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HFSCCD: A Hybrid Neural Network for Fetal Standard Cardiac Cycle Detection in Ultrasound Videos.

IEEE journal of biomedical and health informatics May 6, 2024
In the fetal cardiac ultrasound examination, standard cardiac cycle (SCC) recognition is the essential foundation for diagnosing congenital heart disease. Previous studies have mostly focused on the detection of adult CCs, which may not be applicable...
Neural Networks, Computer Algorithms Pregnancy Female Humans Heart Defects, Congenital Fetal Heart Ultrasonography, Prenatal Video Recording Image Interpretation, Computer-Assisted
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The combination of deep learning and pseudo-MS image improves the applicability of metabolomics to congenital heart defect prenatal screening.

Talanta Apr 17, 2024
To investigate the metabolic alterations in maternal individuals with fetal congenital heart disease (FCHD), establish the FCHD diagnostic models, and assess the performance of these models, we recruited two batches of pregnant women. By metabolomics...
Pregnancy Prenatal Diagnosis Female Metabolomics Tandem Mass Spectrometry Humans Adult Heart Defects, Congenital Deep Learning
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