AIMC Topic: Heart Septal Defects, Ventricular
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Application of machine learning in predicting postoperative arrhythmia following transcatheter closure of perimembranous ventricular septal defects.
Kardiologia polska
Jan 2, 2025
BACKGROUND: Arrhythmia is a frequent complication following transcatheter device closure of perimembranous ventricular septal defects (pmVSD). However, there is currently a lack of a convenient tool for predicting postoperative arrhythmia.
Application of artificial intelligence in VSD prenatal diagnosis from fetal heart ultrasound images.
BMC pregnancy and childbirth
Nov 16, 2024
BACKGROUND: Developing a combined artificial intelligence (AI) and ultrasound imaging to provide an accurate, objective, and efficient adjunctive diagnostic approach for fetal heart ventricular septal defects (VSD).
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...
Aber-OWL: a framework for ontology-based data access in biology.
BMC bioinformatics
Jan 28, 2015
BACKGROUND: Many ontologies have been developed in biology and these ontologies increasingly contain large volumes of formalized knowledge commonly expressed in the Web Ontology Language (OWL). Computational access to the knowledge contained within t...
Leveraging artificial intelligence for predicting spontaneous closure of perimembranous ventricular septal defect in children: a multicentre, retrospective study in China.
The Lancet. Digital health
Jan 1, 2025
BACKGROUND: Perimembranous ventricular septal defect (PMVSD) is a prevalent congenital heart disease, presenting challenges in predicting spontaneous closure, which is crucial for therapeutic decisions. Existing models mainly rely on structured echoc...
Deep learning-based differentiation of ventricular septal defect from tetralogy of Fallot in fetal echocardiography images.
Technology and health care : official journal of the European Society for Engineering and Medicine
Jan 1, 2024
BACKGROUND: Congenital heart disease (CHD) seriously affects children's health and quality of life, and early detection of CHD can reduce its impact on children's health. Tetralogy of Fallot (TOF) and ventricular septal defect (VSD) are two types of ...
Intelligent Phonocardiography for Screening Ventricular Septal Defect Using Time Growing Neural Network.
Studies in health technology and informatics
Jan 1, 2017
This paper presents results of a study on the applicability of the intelligent phonocardiography in discriminating between Ventricular Spetal Defect (VSD) and regurgitation of the atrioventricular valves. An original machine learning method, based on...
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