AIMC Topic: Heart Defects, Congenital

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Deep-learning model for prenatal congenital heart disease screening generalizes to community setting and outperforms clinical detection.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology Jan 1, 2024
OBJECTIVES: Despite nearly universal prenatal ultrasound screening programs, congenital heart defects (CHD) are still missed, which may result in severe morbidity or even death. Deep machine learning (DL) can automate image recognition from ultrasoun...
Humans Pregnancy Female Deep Learning Heart Defects, Congenital Prenatal Diagnosis Infant, Newborn Sensitivity and Specificity Ultrasonography, Prenatal
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Cardiac CTA image quality of adaptive statistical iterative reconstruction-V versus deep learning reconstruction "TrueFidelity" in children with congenital heart disease.

Medicine Oct 21, 2022
BACKGROUND: Several recent studies have reported that deep learning reconstruction "TrueFidelity" (TF) improves computed tomography (CT) image quality. However, no study has compared adaptive statistical repeated reconstruction (ASIR-V) using TF in p...
Radiation Dosage Heart Defects, Congenital Infant Deep Learning Child Image Processing, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted Heart Atria Algorithms Tomography, X-Ray Computed Male Humans
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Heart Murmurs in Children: Evaluation and Management.

American family physician Mar 1, 2022
Up to 8.6% of infants and 80% of children have a heart murmur during their early years of life. The presence of a murmur can indicate conditions ranging from no discernable pathology to acquired or congenital heart disease. In infants with a murmur, ...
Heart Murmurs Humans Artificial Intelligence Child Infant, Newborn Electrocardiography Echocardiography Heart Defects, Congenital Infant
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Deep learning for detecting congenital heart disease in the fetus.

Nature medicine May 1, 2021
Heart Defects, Congenital Deep Learning Fetus Humans Neural Networks, Computer Pregnancy Female
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[Artificial intelligence technology in cardiac auscultation screening for congenital heart disease: present and future].

Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences Oct 25, 2020
The electronic stethoscope combined with artificial intelligence (AI) technology has realized the digital acquisition of heart sounds and intelligent identification of congenital heart disease, which provides objective basis for heart sound auscultat...
Artificial Intelligence Algorithms Mass Screening Humans Heart Defects, Congenital Heart Auscultation
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Prediction of Pulmonary to Systemic Flow Ratio in Patients With Congenital Heart Disease Using Deep Learning-Based Analysis of Chest Radiographs.

JAMA cardiology Apr 1, 2020
IMPORTANCE: Chest radiography is a useful noninvasive modality to evaluate pulmonary blood flow status in patients with congenital heart disease. However, the predictive value of chest radiography is limited by the subjective and qualitive nature of ...
Pulmonary Circulation Humans Child, Preschool Child Radiographic Image Interpretation, Computer-Assisted Male Radiography, Thoracic Retrospective Studies Infant Heart Defects, Congenital Female Deep Learning Blood Circulation
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CHDGKB: a knowledgebase for systematic understanding of genetic variations associated with non-syndromic congenital heart disease.

Database : the journal of biological databases and curation Jan 1, 2020
Congenital heart disease (CHD) is one of the most common birth defects, with complex genetic and environmental etiologies. The reports of genetic variation associated with CHD have increased dramatically in recent years due to the revolutionary devel...
Humans Databases, Factual Knowledge Bases Genetic Variation Heart Defects, Congenital
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[Classification of heart sound signals in congenital heart disease based on convolutional neural network].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi Oct 25, 2019
Cardiac auscultation is the basic way for primary diagnosis and screening of congenital heart disease(CHD). A new classification algorithm of CHD based on convolution neural network was proposed for analysis and classification of CHD heart sounds in ...
Sensitivity and Specificity Heart Defects, Congenital Heart Sounds Neural Networks, Computer Algorithms Humans
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An artificial neural network prediction model of congenital heart disease based on risk factors: A hospital-based case-control study.

Medicine Feb 1, 2017
An artificial neural network (ANN) model was developed to predict the risks of congenital heart disease (CHD) in pregnant women.This hospital-based case-control study involved 119 CHD cases and 239 controls all recruited from birth defect surveillanc...
Diet Case-Control Studies Logistic Models Adult Sensitivity and Specificity Heart Defects, Congenital Reproductive History Socioeconomic Factors Health Status Maternal Exposure Humans Neural Networks, Computer Pregnancy Female Risk Factors
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A Decision Support System for Cardiac Disease Diagnosis Based on Machine Learning Methods.

Studies in health technology and informatics Jan 1, 2017
This paper proposes a decision support system for screening pediatric cardiac disease in primary healthcare centres relying on the heart sound time series analysis. The proposed system employs our processing method which is based on the hidden Markov...
Heart Sounds Software Humans Decision Support Systems, Clinical Machine Learning Heart Defects, Congenital
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